I was an artist sculptor and now I'm diving into deep learning.


How do I stay motivated? - 1000 Subscriber LIVE Q&A

Woohoo! Yes. My goal is to contribute to vote just like you, man. Cheers.


Oh, thank you. It means a lot to me, man. Thank you so much.


It's so good to to hear people who are interested in the similar things.


Sharam, how are you, my friend? Sharam, Jadu, hi. Stefan, Black and Ship.


Here's your shout out, man. Shout out to Stefan. Thanks for joining into the chat.


Andy Mack. Hi, Daniel.


Would you attribute your general positivity and enthusiasm towards self-improvement to the fact you keep physically active and live a healthy lifestyle?


Or were you born with this mindset?


I would say it's a combination of both. See, I hit the jackpot, right?


I'm not going to lie. I hit the the existence jackpot in terms of a human being.


I was born into to Australia. And this is not against anyone else.


Right. I'm just saying how how I see it for myself.


I was born into Australia, which is a very privileged country.


I was born into a loving family with two amazing parents.


And I have three younger brothers who are all awesome.


Right. So I got very, very lucky with that.


I'm not going to not going to doubt that for a second.


Right. So that's that's I think it's a combination of that.


My dad is a very positive person.


He he has had a big influence on me in my life.


He's always been a been a joker, finds the fun in things.


And I think that's that's where I get a lot of the positivity and enthusiasm from being the eldest of four siblings.


I think as well brings a lot of enthusiasm, positivity to me because I'm going to be a leader.


I have to I've got no other choice.


I have to set a good example for my little brothers because ultimately it's it's monkey see monkey do right there.


If I do something bad or if I do some sort of action, ultimately they look up to me.


So I think that there's a combination of that and getting back to the physically healthy lifestyle.


I think that that has to play a factor in it as well.


Right. So I get I use my natural doctors. Let's just say that.


Right. So I try to sleep as best I can.


I eat as best I can. I stay active.


I think those three things like the health pyramid, if you can get those three things down pat, you're you're already on the right path.


Right. I honestly believe you just get sleep, eating, movement down pat.


And once you've got that, once you've got your health, you can health is another one factor.


Right. Once you've got that, you can you can use your health to to propel you through other


fields in life. So I've got a I've got a motto or a lot of people do actually, but I've stolen it from someone else.


Never trade your health for wealth. Right. So a lot of people live a life.


You'll see in history where they've spent their youth growing up, trying to make as much money as possible,


trying to be as as as rich as possible, be as successful as possible.


They do end up making a lot of money. But then by the time they're 40, 50, 60 years old,


they're spending a lot of that money recuperating the health that they lost because they burnt it out over those years.


So I think a combination of all that being extremely lucky, being healthy, definitely contributes to to my positivity.


And I think the number one thing as well or one of the number one things is just being happy to be here.


Like we're we're here. We're on Earth. Right. We're alive.


We hit the we hit the jackpot. We could have been a bus, but instead we get to laugh.


We get to hug each other. We get to smile. We get to we get to kiss.


We get to eat amazing foods. We get to drink amazing drinks.


It's it's amazing to be alive. Right. And don't get me wrong.


Life is is hard by definition. It's hard, but. It's binary again.


Right. If you can either accept the fact that it's hard and enjoy that or you can say, oh, well, I've been a victim of life.


Life just kicked me down and whatnot. And so I think that's where my my positivity and enthusiasm comes from.


It's been a combination of healthy. I got extremely lucky and I'm grateful for that.


And I'm just grateful to be alive. I'm grateful to be here.


I'm grateful for you guys. And that sounded like a grateful porn.


But it's it's the truth. What else do you have? What else do you have?


What do we have here? Have I ever been in a tornado when you were in a house?


No, but my house in Brisbane, Brisbane is a tropical city in Australia.


Not a fully tropical city, but there are some heavy, heavy storms in Australia and Brisbane.


Thunderstorms, hail, you name it. But my house is made out of bricks.


So it doesn't really get blown over like in there. What's it called?


The three big bad walls or something like that. But no, no tornadoes in in where I live.


Maybe a bit north in Cairns or something like that in North Queensland.


They they suffer or they tornadoes hit them all the time.


We have Siri Boff. Siri Boff, how are you, mate? Nice to meet you.


So what do you think about learning quality of ML or data science at university versus Udacity versus Coursera?


OK, well, I can't comment from learning it at university, but I will say here's how I made my decision.


I graduated with a with a science degree in 2015.


I spent the next year learning Mandarin and Chinese and Japanese.


Right. I had a great time. I was planning to go to Japan with my girlfriend.


So I was learning Japanese, but we broke up. I went to Japan anyway.


Sort of had a self-discovery moment over there. I was there for about a month.


It was an amazing trip. I still got a Japanese poster on my wall, which you can't see.


But amazing time in Japan. And then I realized, hey, I'm really loving this technology stuff.


I want to start learning it. So I started looking.


I Googled Masters of Computer Science at my at my old university, and it was like 40 something thousand a year.


It was two years and it was all these subjects I didn't really like.


Then I just went on Google and looked up how to learn coding online.


I started with Treehouse and it was twenty five dollars a month.


And I'm like, this is a no brainer. I'd spent five years at university.


I failed the first two years. I had to explain to my dean why I should still be at the university.


But then once I got back, I learned how to learn.


That's how I spent my time at university learning how to learn.


And I believe that is one of the most valuable skills you can ever have, because once you understand how you learn,


you can apply that to anything. You can learn whatever you want.


So I looked at university courses for computer science and whatnot. Way too expensive.


Wasn't what I wanted to be studying. Whereas I went online and I'm like, hold on.


These are far cheaper and I can control exactly the courses that I do, exactly the order that I do.


And it's going to be completely up to me whether I complete them or not.


So I just said, I'm going to take the leap and I'm going to jump in.


So university, don't get me wrong, is still probably great for for learning this stuff.


However, the field, as you all probably know, the field of data science, the field of machine learning,


the field of artificial intelligence is changing every single day, whereas universities can't really keep up with it.


They can't. Right. So they have to they make a curriculum and it stays the same for the next year.


So the professor can teach it. But if you go online, Udacity, since enrolling in the deep learning degree last year,


they've updated the course, I think three or four times. Right. Universities can't do that.


You can go to YouTube and learn the latest and greatest and deep learning from someone like Saraj or someone else that has actually been released in the last week.


So I think in terms of flexibility, online learning is is the best, in my opinion.


But in terms of traditional style, maybe you want to go to university.


But honestly, I would definitely if you can if you can learn on your own, go the online route, my friend, because because you can design your own course,


you can change it on the fly and it probably won't cost you anywhere near as much as what university is.


And the courses I've done on Udacity and Coursera are the best courses I've ever done.


And I went to university for five years. Have I ever met a fan?


Oh, good question. I think I think I might have.


But a lot of my fans are from overseas.


And that's the beautiful thing about YouTube is that it connects all over the world.


So I have people from India, from the United States, from from Europe, everyone joining in to watch this.


Right. And if I'm honest, there aren't many people that I know that live locally


that know or that are interested in what what my channel is mostly about, which is AI, I guess fitness.


People love fitness. Right. But but a lot of it has been about that AI and machine learning and whatnot.


And if I'm honest, there's a minority at the moment.


Like there's not that many people who are interested in it locally.


Don't get me wrong. There are there are a few, but nowhere near as many as what I'm seeing online.


Right. Here we have glad things are going great for you.


I'm going to head to bed. God bless you all. Night.


Class center. Oh, my puppy just joined in the room.


You can probably see her tail here. So keep learning.


Yes, Asher A.


Jane, keep learning. And what are my sources for learning new stuff in ML AI?


At the moment, it's it's YouTube, it's blog articles, TechCrunch, Medium.


Probably Medium is number one.


Medium is just amazing. Go to medium.com and look up whatever you want on their emails.


Who was it? Jack? Jack someone.


If you look up Jack, Google Jack, I email, he will send you a bunch of different stuff.


There's another guy, Benedict Evans, who sends out a lot of technology stuff.


But otherwise, yeah, YouTube, Medium and email newsletters.


They're the three main. So if you just Google AI newsletter, I'm sure you'll get a bunch of different things.


And I've been thinking about starting a podcast of my own, actually.


Put a comment in there in the in the channel in the chat.


If you'd like to see me do a podcast of some sort around AI,


whether I would talk about what I'm learning, the latest stuff in the field, interview people from the field.


So I'd go and interview machine learning engineers or engineers or something like that.


If podcasts are your thing, let me know, because I've been I've been playing with the idea in my head for a while.


And format would be somewhere between 15 to 30 minutes in terms of length,


because I like I think I can get a few topics out there.


But yeah, interviews are probably a bit longer, so maybe an hour or so, depending how much I can get.


So that's definitely something I've got in the pipeline. What do we have here?


What am I? Stefan, have you ever had surgery or have you ever failed an M.C.A. test?


I'm not entirely sure what M.C.A. is, but I've had surgery.


I had surgery on my eye when I was 10, I believe.


So not nothing bad. It was some sort of cyst on my eye.


But I remember my eye was sore for months. It sucked.


I had my appendix out. I had my tonsils out.


Was the first patient ever in Australia or something like that to bleed from both sides on my tonsillectomy.


So I had the surgery nine days later. I got in a hot shower and I had blood dripping down from one side.


Two days after that, after getting that side fixed, I had blood dripping from the other side.


I'm apparently the first patient ever. Maybe that's changed.


Then I had my appendix out. I didn't actually need to have my appendix out.


So bonus thing is I'm pretty sure I'm qualified to work in Antarctica now because I don't have an appendix or tonsils,


which I believe I'm not entirely sure. Don't quote me.


You can't have if you go to work in Antarctica.


How do I keep myself motivated when the going gets tough from Sharan?


As I said from before, it's to me, I just think about the alternative, Sharan.


It's it's what what other option do I have? All right.


It's going to get tough and I've just I've kind of just accepted that.


Right. It's going to get tough. So I have that mindset of I try to.


I try to have that mindset. Don't get me wrong. I'm still I'm not perfect.


I'm not special. I just I just know that when I go to do something new, it's going to be tough.


And eventually when the momentum stops going, when the new causes that the newness, the shininess wears off, it's going to get tough.


But that's that's exactly why I'm doing it is because it's tough.


Right. And not everyone, not everyone can do that.


So if you can just push through that toughness and think about what the alternative is, is what's the alternative is just not doing it.


Everyone can take that. Not many people can push through the toughness.


So that's what's going to differentiate you. It's going to not even you from other people.


It's going to differentiate you from your past you, which is the only competition that you really have.


Andy Mack. Thanks, Daniel. You've come a long way since the St.


Pat's Day's. Hey, thanks, brother. If you could can't fly, then run.


If you can't run, then walk. If you can't walk, then crawl. Keep moving forward.


That's right. That's what we're going to do. We're going to keep learning. Thanks, brother.


Cheers. Everyone's loving the podcast. I think this might be a thing, guys.


I think I think we might we might get it on. So I'll I'll I'll get it.


You'll find out if it comes out. Have you ever been in a relationship with an abusive person?


No, I've been in one relationship with a I had a girlfriend for two years and she was amazing.


She was, you know, no complaints about her. We broke up.


Just the relationship fizzled out, which was really hard.


It sucked because I was still loved her. But that's that's life. Life goes on, right?


So, yeah, no, I got lucky on that department, too. Amazing relationship.


Hi. Hi, Galshan. Nice to see you, man. Thank you. Welcome. Good to see you, my friend.


And I just graduated from deep learning nanogree and received the certificate today.


I want to know what did you do between DL and AI Nanogree? Any advice before I roll in AI?


In in in between the DL and AI Nanogree, I believe I did the deep learning.ai course.


And or some other filler course. Now, if you if I've actually documented everything that it is,


and it's kind of funny that I can't remember it, but that's exactly why I'm documenting it.


So if you want to go back to check out if you Google how I'm learning deep learning, Daniel Burke,


there's there's all the articles detailing step by step what I've done.


Videos will be there as well. So I think I did some sort of little mini course in between.


Maybe, maybe not. I can't confirm. But if you've just graduated,


I would say the best thing you could do is just go over your what you've learned,


write an article about it, because it will re re rewire it in your brain to learn it even more.


And then share that online. That way, if someone asks you, how was the course,


you can send them in your article, because you've wrote what you've learned on there.


So I think it's a great thing to do in between in between courses is to summarize what you've learned


from the previous one before jumping too quickly into the next one.


Cerro Brough, thank you. Thank you for it. I feel bad for you. Stay determined.


Stephen, stay strong. I will. I will. I am strong. I am strong.


But we're going to go to a saved question that I have here.


So if you have any more questions, people in the live stream who are watching now leave one here.


But otherwise we have Rui. I'm thinking of taking the Udacity AI nanodegree.


So I want to hear your opinion about it. Are the projects industry level?


Do you think they will help land me a job in the industry if they are only projects on my resume?


Yes, I definitely, definitely believe they are industry level.


Udacity partners with with some amazing companies who are actually working on this tech


day in, day out in a commercial setting, and they create the projects based on on what they've


learned from the industry partners. And a case in point, I was offered a role at a data science


slash machine learning company based off what I've been learning. And I've done the Udacity AI nanodegree.


I'm going to call the CEO tomorrow morning to discuss more further details.


It's been at the place where I've been doing the internship. But of course, whether I get the job,


or whether I don't get the job, I'll let you know. But I truly believe that if you do have a Udacity course


on your resume, it will help you out get a job in the industry. However, don't just think that the resume is enough.


There's so many people, I think, believe that just having things on a resume is good enough.


If I was I think about if I was going to hire someone for my company or my startup of some sort,


I would be looking to see what else you have apart from a resume, right? Because I'm of the opinion


you should be focusing on building a life rather than building a resume. So don't let a piece of A4 paper,


one sheet of A4 paper dictate who you are in life. This is my honest opinion.


I'd rather you not even have a resume. Send me your blog where you've worked on


on different projects, you've written articles about AI, you've shared what you've learned.


And I think that is more valuable than a resume. So of course, having a resume is still the traditional way of doing things.


I think it's a load of crap, just in my opinion. But have a pimped out LinkedIn profile,


have a blog of some sort, or have a portfolio of works you've done that you can easily show


someone else. GitHub is another great resource. So to go back to your question,


that was kind of a long-winded answer. Yes, the Udacity projects are industry level.


And yes, I believe they will help land you a job as long as you have a resume and something else


to differentiate yourself. A GitHub account, LinkedIn, blog. If you can have all of them,


you're really, really on the right path. And then we'll do one more from here and then we'll go back to the chat.


So we have Lakshmi who has asked, I'm starting my journey in machine learning, much interested in AIML.


Could you please help suggest me in growing my career path? So Lakshmi, I believe I sent him back


my article of how I got started in it. But it really depends.


So I don't have all the answers. So for career path, I'm still trying to work it out myself.


But what I believe is very powerful if you want to decide what you want to do for your career


is have a look, write down on a piece of paper, do a timeline. Actually, let's use the white


board. It's right here. So have a timeline. You got where you are here. Let's say you're a circle.


Right, if this is what you want your career path to do. Now, I would say three to five years is a good


timeframe, especially in this industry, because it's changing so fast. So three to five years,


just imagine where is my ideal place? And I mean, it could be as big as going, I want to be


the CEO of my own tech startup, which is very, very well and truly possible, right? If you work


hard enough, and you have the skills and you find the right people. So this is career path advice


from beware, this is from someone who is still working it out himself. But this is how I approach


it. So you start here, this is where you are now, right? This is all you know, this is all your


relationships. This is everything you own, all in this one circle, then I would put your goal three


to five years. So three to five years. This is the most ideal scenario you could possibly want. And


if it appears backwards on the screen, guys, I'm sorry, but just imagine this x is three to five


years from this dot. Now, ideally, you could go walk in a straight line and go here. Right?


That might work. But in reality, it's probably going to be this kind of this kind of pathway,


you probably circle back a few times, come up, come down, get in there. And then we're going to


end up there. Right? You may end up there, or you may end up at this, this x down here, which is


something totally different. Right? So now it's just a bunch of squiggly lines. But how can you


try and get that straight line? How can you try and get that path? Well, one mindset you can have


is to take where you want to be in three to five years and work backwards, instead of working


forwards from this dot. Now, of course, caveat, working backwards does not always work. But it'll


allow you to best decide what the next step is. So for example, my three to five year goal is I


want to be a paid creative, right? I want to keep doing YouTube, I want to keep working on my own


things. And as part of that paid creative, I want to have my own AI and tech health tech startup.


Will this change? Possibly. But the direction I'm heading is AI health tech startup. So at the moment,


I think my best pathway to get to there is by learning the skills that I'm learning now, getting


experience in the industry, and also keeping myself fit and healthy. Because after all, would


you buy a health health product from someone who wasn't healthy? That's just that's just how I think


right? I personally wouldn't do that. So I myself is the product. Right? So if you're looking for


Korea, this is to Lakshmi. Thank you for the question. Think about where you'd like to be in


three to five years. Don't go too long, because that's just you can't plan that far. You might be


able to but that's just to me, that's way too far. Three to five years, go backwards. Think about


where you are now and think, well, it's the best step I can take to get to that place in three to


five years. That is exactly how I'm thinking about where I want to be in in the future and my career


path. Let's go back to the chat. developer 404, which is my boy Shaik. Welcome, man. Thank you.


Good to see you here, my friend. But how to focus just on one thing learning instead of looking at


phone watching YouTube videos. I totally agree. It is hard to focus. I get distracted all the time.


There's so many good things. There's so many good apps on the phone. I just want to watch everything.


But it really takes away from you. There's some statistic, I don't know how long it is,


but when you get distracted by one thing for 30 seconds or something like that, it takes you 20


something minutes or whatever. I don't know what the time is, but a long time to get back into the


zone, back into the focus. I just think if I'm trying to get the most out of my time,


while I'm learning, then I'm not going to waste three seconds to look at an Instagram post


just to take another 20 or so minutes to get back to where I was learning.


It just takes practice. At the start, you might only be able to go 15 minutes without


getting distracted. But I've slowly worked up and don't get me wrong, it's still hard.


It's still really hard. It's so fucking hard to concentrate, but that is exactly what it should


be. I think a lot of people look too much for the easy way out. The truth is, you can take the easy


way out in terms of just looking at your phone and learning and whatnot, but ultimately, that's going


to distract you from where you want to be. I'm not about that. It's just like, I want to do this,


and that's all I'm doing now. A really, really easy way is I put my phone in the drawer,


in a drawer so I can't even see it. If you can see it on your desk, it's probably going to distract


you. You can download apps on the computer like self-control for Mac, I believe is one,


where you can block websites entirely. That's one way. I turn off all my notifications.


I even put my phone in another room. There's ways to do it, but our brains,


we're wired to want to look at these things because it tells us things we want to hear,


makes us feel important. It's not fair. There's a thousand engineers working in Silicon Valley and


US trying to make these as addictive as possible. Maybe they don't think of it as they're trying to


make it as addictive as possible, but ultimately, when you look at the psychological tricks that


they use to make you spend more time on the apps, it is making them addictive, essentially.


Realize that they can be addictive and that it's just going to be a battle to get used to


not being distracted by them while you're working on what actually matters. If you want to get


better at it, start small, 15 minutes today, do that for a week. Then the next week, you've done


your 15 minutes, you don't look at distractions, and then you do 30 minutes. What I think is also


important is to not be so strict on yourself that you don't want to be distracted by them.


Don't be so strict on yourself that you get angry if you don't do it. Just be your own biggest fan


and your own worst critic at the same time. What I mean by that is if you've done 25 minutes of


study, give yourself a little reward. Maybe you go for a five-minute walk or maybe you can watch


that YouTube video now or something like that. That's how human beings work. We do a little bit


of work and we reward ourselves and it reinforces that work behavior, like a reinforcement learning


algorithm. That's a good analogy. Treat yourself like a reinforcement learning algorithm. If you're


doing the wrong thing, not good. If you do the right thing, good. We have a fair few things in


the chat. Where were we up to? What am I going to learn? When am I ending the stream? It's daytime


2.25 pm. Stream will end. I don't have a time limit. We're going to keep going. I'm having fun


here. Are you guys having fun? Is this all right? If you want to see something different from me,


just let me know. I'm getting through the chat as quickly as I can. I kind of spent a bit too long


on the answers, but I try to give you as much thought as possible in these longer form videos.


I'm trying to keep my YouTube videos under 10 minutes, maybe six to seven minutes. How do you


like that length? Is that a good length? Do more of these longer form talks every so often to answer


some more in-depth questions. What do I plan on doing next? Hey Anush, how are you mate? Nice to


see you. Thanks for joining in. What am I planning on doing next after the AI Nanodegree? According


to my AI master's degree that I created, I'm going to do the fast.ai course, which I'm actually really


excited for. I've been looking at it. It's been updated. If you haven't seen it before, go to


fast.ai. It's a free course on AI. I think it's just been all rewritten in PyTorch, which is


exciting. I haven't had much experience with PyTorch. If you're not familiar with PyTorch,


it's a deep learning library. Karan, thank you so much my friend. Really, really appreciate it.


Thanks for being on this journey. We have Andy Kishore. Are you excited for Earth Day? Yes,


of course, but I'm afraid, I'll be honest, I don't know when Earth Day is. I used to work at Apple.


We celebrated Earth Day there every year and I loved it. I just think it's binary again.


It's don't damage the environment. We need the environment to live. If you can do something


to bring value to the world and also not damage the environment, that's what you should be going


for rather than non-renewables. I just don't understand and don't get me wrong, I'm not a


saint. My house is not powered by renewable energy, but I am definitely a big proponent of it. I 100%


believe that it's the only way we'll ever keep going as a civilization is to respect the Earth.


It's simple, right? What am I currently reading? Where are my books? Here we go.


Great Gatsby. Awesome book. I've been reading this for a while actually because I read it late at


night when I'm about to go to bed. I like to read nonfiction before I go to bed just because I like


stories. It's human nature. We like stories. I'm really liking that. I just finished reading


Crushing It. I'm listening to it again on Audible by Gary Vaynerchuk. Awesome dude. Awesome book.


If you're looking to learn more about marketing and creating digital content,


check out Crushing It. Highly recommend. I got a whole bunch of other books here as well.


Actually, if you want to find out what I'm reading, go to mrdburke.com. Everything's there.


Those two are the main two at the moment. Then we have here, is the internship paid? No. The first


three weeks I've been there, it's only been one day a week, but it's not paid. That is exactly


what I was going for. I am grateful for the experience. That being said, the internship


is converted into an offer to come on for a paid role. Tomorrow morning, as I said earlier in the


stream, I'm going to be calling the CEO to discuss role options, pay options, what exactly I'll be


doing. Of course, once I find out more, I'll share what I can. Maybe there'll be some details that


will be in the contract that I can't share, but who knows? I'll let you know if it happens or


doesn't happen. The internship, not paid. Hey, man. Congrats. Thank you, my friend,


Discover Artificial Intelligence. Then we have, have you seen your channel? I don't think I have,


but that's awesome. Awesome. That is, hey, do I want to do a collab? Yeah, man. I'm happy to do


Skype calls and whatnot. Otherwise, if you have any ideas on collabs, email me, daniel


at mrdberg.com. You'll be able to find my email or just Google my name. You'll find something. I'm on


the internet everywhere. Stefan, thank you so much. I'm loving it. Have I heard of Undertake,


Undertale? No, I haven't heard of that. When you always fail and you fall down, always try again


and get up and you'll succeed. That's the most, that's the point, right? No failures, just lessons.


That's the quote I live by. Now we're going to go to a question over here. So I had, I can't remember


who it was from, but someone asked me the credibility of AI and other online courses.


Credibility, if you want a perfect example, I've been offered roles in data science internships


and AI technologies and I've only specifically done online courses. And I think if you're asking


about the credibility, it's the wrong question. To me, that is the wrong question to ask, right?


Because I just think how the world's moving, right? If I was a CEO, if I was someone looking to get a


good person to work for my company, what would I be looking for, right? Credibility, yeah, so what?


Like some universities may be better than others, but ultimately, can I relate to you as a person?


Can I see the fact that you can potentially look at a problem, break it down in different steps,


use the accumulated knowledge you've formed over your years of life to solve that problem? That's


what I'm more worried about rather than the credibility of, have you done this course?


Have you been to this university? Have you paid $100,000 to this person? No, no, no, no, don't


care about that. I care about the fact that you can do good work. And that's, that would be my


opinion as a CEO, right? So when I held a company, when I had my company and I'm CEO and founder,


and I'm hiring someone, all of you guys will get preference, right? I don't know. I'll say that now,


and that might have to change in the future. Who knows? I've never run a company before.


But I will not be caring about the university you went to. I will be first and foremost caring about


whether you've put yourself out there and tried to do some awesome work,


right? And whether my team can work with you, and whether you can work with my team. Because


ultimately, if the relationship doesn't work, then no one's going to win, right? That's the most


important thing when you go to an interview or to a new job or to build your own company,


build a great team, and everything else will fall in place. It might not because you might fail.


But usually, if you have a great team in place, you'll work things out. So credibility, don't


worry. Just get the knowledge, build some awesome shit, and that's what matters. Merlin asked,


what do I do when I get sad? I just, I remember how lucky I am, man. This is the truth. That's it.


It's just, why do I have to be sad? And don't get me wrong, sadness is meant to be felt. Same with


pain, right? There's no such thing as a life full of happiness, right? If you didn't have pain and


suffering, there would be no such thing as happiness. It's the yin and the yang. You have to


experience pain to be able to enjoy the happiness and the good times, right? So that's what most,


I think that's sort of underestimated in life is people are like, oh, we should always strive to be


happy. We should never be sad. We should never be down. We should never be whatever. You see me,


I'm energetic. I'm enthusiastic. I'm positive. But I still get sad. I still wake up sometimes and


think, fuck, I don't want to do shit today. But then I realize, what's the alternative? I could


just sit here all day and complain about the fact that I don't feel that great. Or I could get my


body moving, get some movement, get some food, get some water, study some things, create something.


And all of a sudden, I beat the sadness out of me, right? But because I've experienced that sadness,


I now relish of how good a happy feeling feels, right? If you didn't feel the pain,


the happiness would not feel as good. So when I get sad, I just keep moving. I keep moving. I drill


down. What's the sadness coming from? The sadness is coming from me not being true to myself. That's


the number one reason every fucking time. It's when I'm not true to myself, when I'm not doing


what I know my mission is. And trust me, the mission is still getting reevaluated all the time.


But that is when I'm sad the most, is when I'm not doing what I know to be true to myself.


Merlin also asked, how do I stay motivated? I've answered that earlier in the stream,


so we won't go back to that again. Kumar, how are you, mate? Thank you for that question.


How old am I? I'm 24. I turned 25 on September 1st. So send me a happy birthday message on


September 1st, 25. I really appreciate it. But we'll probably do a live stream for my birthday


or something because I'm really having a good time here. What are future Dan's glasses? Where are they?


Oh, let me just check. Future Dan, can you make an appearance? Where are they? I don't know.


I can't find the glasses. Yo, what's up, guys? Dan's just taking a break. Future Dan here. 2048


is looking amazing. And I know you just heard me sing, but that's all right. That's all right.


I'm going to do these things sometimes. You got to have a little fun with it. Let's get some


questions on. What do we got here? I am Alessari. Check out my YouTube channel for tutorials.


Hey, man. Hey, guys, check out this guy, Alessari. He's building some awesome things.


Here we got here. Daniel, try to be a bit quicker with my answers, please.


Yeah, I know. Daniel talks so long. He's quick. Let's do some future Dan answers because I'm a lot


quicker than Dan. All right. So we got Horace off. Daniel, are you using deep learning neural


networks with your internship? Yes. Done. We have someone else here. Am I trying to find an


internship? I'm trying to find an internship in machine learning. But here in India, there are not


many opportunities. Any direction you can show me. If you want to find an internship, start messaging


people every day, every single day companies you want to work for message them, ask them for their


advice and say, Hey, I'm trying to learn I'm trying to get an internship. What's your advice?


More often than not, no one will reply. Maybe one in 10 will go here's things you can do. Maybe one


in 50 will be like, I know someone who can get you an internship. Message people on LinkedIn all day


if you're looking for an internship or a job. How do I get into AI from Merlin? I started web


development and failed to start up. Well, really didn't fail it. It was just laziness, but learned


that AI is the future and was fascinating. So yeah, and I think we just cracked the hour mark. So


I think it's time to wrap this up. But I'll go get down. Oh, what just happened? Anyway, um, oh,


we are over an hour. Guys, thank you so much for joining in. It has been amazing. We this channel


is is just beginning. There's going to be so much more. It's the first 1000. That's my only number


goal. I'm putting it out there. Go by the end of here will be 10k. So let's do it. But as as you know,


my dog is barking. Bella, Bella, come on. Can you see it? That's my dog. That's Bella. But I'm going


to sign off Bella and I are going we might go for a walk actually. No, don't get excited. Don't get


too excited because I think I have to go to gym. But thank you so much for joining in. I hope you


enjoyed this video. If you did, please give it a thumbs up and subscribe to my channel.


I'm going to see you next time. Amazing journey. And of course, as always, where is it? Where's my


I haven't been ever ever been arrested. Not yet. Anyway, never say never. Right. But peace, brother.


Thanks for tuning in. The whole video will be archived. Because it's illegal to look that good.


Every model I build has to answer 1 simple question | Airbnb Machine Learning Project Part 5

Would you look at that? We can tick off week two of the 20 friendly-ifying Airbnb's object


detection pipeline. We are up to day 15. Hey look there's a bug, checking it out.


Week three, how exciting! Let's go over and check out the whiteboard, the whiteboard of


peace like my personal assistant. We need to first of all update this as usual. Day 15.


Oh that doesn't really look very good but that's alright. Progress not perfection. Okay,


so week two we can take that off. In the last video we built a small model. So we've got a


small model working so that is really amazing. Week three, refine data sources. I'm going to


bring this down into here because we want to get all of our images ready in week three.


And start scaling up model with data sources. Well that would make sense if we refine the data


sources first aka get rid of get all of OpenImage's images ready for Detectron 2. I'm going to put


another one here. Track experiments. Track experiments is because I'm going to probably


be building multiple models. How will I know which one performs best? What type of settings


I'm using? Hyperparameters? That sort of stuff. And so let me show you what I've got in Notion


planned out for this week in terms of how I plan to do that. So it is officially week three as


dictated by the Notion board. I got here code refactoring, downloading all the data and model


scaling up. So we got our small model built last week which is amazing. So this week we're going


to start to scale it up using more data because the model we built last week was only using a


very small subset of the data. And so this is how I plan at the start of my week. Download and


convert all images and labels to Detectron 2 style labeling. Track experiments with weights and


biases. Now weights and biases is a tool that I've been really looking forward to use in one of my


own projects. So I'm actually 10 out of 10 excited to try and use this. It's a tool that you can use


to track your different experiments with machine learning models which is what I'm going to do here.


Because as I said before it's important to know what worked and what didn't work.


Scale up model to work with more than one class. That's going to build off the back of this


downloading converting all images and then clean up my crummy code. So the code I wrote over the


past two weeks could definitely be improved so I'm going to try and start doing a little bit of that


now. But because today is Monday and Mondays are research Mondays I'm going to be researching ways


to track experiments aka mostly looking at weights and biases. I've got an article here


of one of the tutorials because Detectron 2 is built in PyTorch I'm going to just check out the


weights and bias article. Intro to PyTorch with weights and biases. So that's how I'm going to


start. I think the first half of this week is going to be setting up experiment tracking and then the


back half of this week is going to be scaling up the model on all the data. That's my rough idea


for how this week's going to pan out. May turn out that way may not but anyway welcome to part five.


What could we call this one? Tracking experiments.


We are on day 17 and the reason why I love the number 17 is because I have a dog named Seven.


So Seven is kind of my lucky number but let me give you a quick update of where we're at.


Actually the Notion document is probably the best place to start this so I'll just show you exactly


what I'm writing I'm thinking about. So you can see day 17 let's figure out how to create my own


Detectron 2 training loop which tracks results. And so I had an idea yesterday we linked down to


this. My idea late yesterday day 16 which was one of those days I'll put it here today is one of


those days where I'm trying to figure something out I'm not sure how long it'll turn out. I know


what I'd like to get done and that's a way to have and that's have a way to track the different


experiments I run. We'll probably only get a good hour or so in today because yesterday


as you can see life got in the way so I just had to work around that but these things happen right.


So yesterday I didn't get too much done other than just read through a bunch of Detectron 2


documentation which actually turned out to be really valuable because that's when I got this


idea the end of late yesterday. So merge plane train net.py my Detectron 2 code and the weights


and biases PyTorch example notebook into my own Detectron 2 experiment. And so that's what we're


trying to do today. So you see here 12 56 pm which is about now. Let's see what happens when we try


to merge plane train net.py a Detectron 2 script my own Detectron 2 pre-processing notebook and the


weights and biases PyTorch example. So long story short I'm trying to scale up my Detectron 2 models


and so I thought the easy option is to just start building a larger model with all the data. But


where's the fun in that right? What if something goes wrong? Where am I going to look? What if I'd


like to improve something? So rather than just scaling the model up straight away what I'm going


to do is sort of build in a little bit of redundancy because I know a small model will work.


So I'm going to get a little bit more familiar with the training process and see what happens


when I create my own training loop which is what is provided here. We come into the Detectron 2


documentation or the Detectron 2 github in plane train net.py. So Detectron 2 training script with


a plane training loop. So I've been reading through this but again always remember that


you're a lot smarter when you're actually doing something than you are just thinking about something.


So yesterday was all about thought for me today is all about doing. So I'm pretty lucky I'm going


to get a few hours of good coding in at least I hope who knows what could happen. But essentially


what this script does is it gets a Detectron 2 model based on some sort of config file,


creates that Detectron 2 model, it has a function called do test and do train. And so the do train


trains your Detectron 2 model and then the test does inference on your model to see how it goes.


And so what I'm looking to do is because I want to incorporate weights and biases to track my


experiments is I want to basically refactor this notebook with my own Detectron 2 small model


building custom data notebook with the introduction to weights and biases PyTorch notebook. So that's


a mixture of three different blends shaken not stirred. So we'll see how this turns out as you


can see I've kind of just took the intro to PyTorch with weights and biases and created my


own version. And I know I'm kind of just blazing over this at the moment but what I figured is


because it's day 17 I'm going to spend the next few days working on this and then we'll see by


the end of this video who knows where I'm going to get to. But what I'll do for day 21 I think is


just like an extended long video maybe a live stream you'll see you'll see it on the channel


when it comes up whatever it is of just walking through the code step by step of where I'm


thinking what I'm doing how I think about things and if it's a live stream that way you'll be able


to ask questions. So without any further ado I'm going to pay attention to my second brain here on


my personal assistant and see what happens when I try to merge plane train net.py my own Detectron


2 pre-processing notebook and the weights and biases PyTorch example. I'll see you when I have


a pretty significant update. Fingers crossed. Welcome back we are finally back can you believe


it it is day 19 of week 3 so the last day of week 3 Friday and at the start of this week we set out


a few goals so that's where the start of this video started. This week we wanted to download


and convert all images and labels to Detectron 2 style labeling. Well I haven't done that.


Track experiments with weights and biases we'll come back to that. Scale up model to work with


more than one class. Haven't done that. And clean up my crummy Detectron 2 code. Haven't done that.


Potentially have made it what's this error doesn't matter potentially have made it a little bit more


crummier so I've got a bunch of refactoring to do but the good news is I said we we did have kind of


two overall goals for this week if we could do it and that was to be able to track experiments


and to scale up the model that we've got working at the same time as tracking the experiments aka


trying different models trying different sets of data trying more data the good news is we've got


one of the two and that is that we have built in an ability to track experiments with weights and


biases but that did not come without any gargantuan effort I mean it took a lot of effort I mean


hours and hours and hours and hours of me just basically bumping around different documentation


trying out code seeing if it works trying to merge a whole bunch of different scripts together


into my own but the good news is we have I can't believe this timing we always get the breakthroughs


at like like Friday afternoon I ran into another CUDA error but we got that solved because you know


the thing is nature's going to throw these challenges at you and you have a couple of


options you can either attack it with effort you can be like the man rowing a boat the man rowing


a boat uses effort or you can just let it happen and be like the man who puts up a sail and uses


magic to travel around so that's what we did we used magic we fixed our CUDA error and we finally


got weights and biases working to track experiments if you're wondering what weights and biases is


it's like a plug-in tool that you can plug into your code works with basically all of the deep


learning and machine learning frameworks that you'll use and it creates this cool little


dashboard where you can track things like different metrics in my case I'm tracking I believe it's the


loss and the average precision they're the two metrics I'm tracking at the moment at the moment


my dashboard is pretty primitive but nonetheless it is set up it is working I've got a custom


training loop for Detectron 2 yeah a custom training loop so all of these things I'm gonna


be fixing next week to scale up the modeling basically moving what we didn't complete from


the whiteboard in week three aka start scaling up the model with different data sources and


download and prepare all the open images to week four because we can tick off track experiments


win-win with all that being said I figured there's almost too much for me to go through in these sort


of short style videos so what I'm going to do is after this one comes out because by the time the


next video comes out we'll be halfway through the 42 days project so 21 days so the halfway point I


think it's a good time then to do like an in-depth video where I'll go through all the code and what's


happening and potentially even live stream refactoring it all because that'd be a bunch of


fun wouldn't it nonetheless the takeaway from this week is to if you're working on your own machine


learning projects have a way to track your experiments like what I'm doing with weights


and biases you might want to check it out there'll be a link in the description that there's a bunch


of tutorials that they've created that's that's what I've used to build mine track your experiments


so you know what works and what doesn't that's what we're going to be doing next tracking our


experiments whilst we scale up our models with more data and different models because every model I


build goes through a series of rigorous tests all to answer one simple question is it a banger how


many bees per minute how many drops how dope are the drops were any acoustic instruments used if so


it is not a banger make sure you tune into the next video where we will find out the answer to


that question it will officially be week four of the six-week project 2025 airbebs object detection


pipeline anyway it's friday night you know what that means i'll see you next time


i once accidentally downloaded the lumineers song i had to throw away my whole computer just to be


We Finished Spartan ULTRA 2018

43 days out. What do we got tonight brother? Quick little 8k. The trifecta is not here. Not here Zeno. What are you doing?


We Finished Spartan ULTRA 2018

43 days to go. Spartan Opera.


We Finished Spartan ULTRA 2018

That late night workout was your number for this one. It was a tough one. 35 days out from Spartan Race.


We Finished Spartan ULTRA 2018

But we got it done. Three weeks out. 20 days out. Did not feel like training at all today.


We Finished Spartan ULTRA 2018

But we got it done. Eight days out. Early morning 10k done. We're gonna do another 10k this afternoon.


We Finished Spartan ULTRA 2018

I'm gonna go get my coffee and then we'll see you guys in the morning.


We Finished Spartan ULTRA 2018

Woo!


We Finished Spartan ULTRA 2018

There's the one.


We Finished Spartan ULTRA 2018

Let's start that again.


We Finished Spartan ULTRA 2018

We're doing a race now.


We Finished Spartan ULTRA 2018

Oh no no. I looked here and I was like, that's just an octoled empty.


We Finished Spartan ULTRA 2018

No, you missed it.


We Finished Spartan ULTRA 2018

Oh, that'll do.


We Finished Spartan ULTRA 2018

We're not doing it again. We're not doing it again.


We Finished Spartan ULTRA 2018

It's 4.35am and you know what zero means on that?


We Finished Spartan ULTRA 2018

What does it mean Zeno?


We Finished Spartan ULTRA 2018

It's race day baby.


We Finished Spartan ULTRA 2018

How are you Rosie? You keen bro?


We Finished Spartan ULTRA 2018

What do you got there man? What's this?


We Finished Spartan ULTRA 2018

Just another day. A bit of band water and a plastic cup.


We Finished Spartan ULTRA 2018

So we're getting our gear ready.


We Finished Spartan ULTRA 2018

Gonna have a little snack before we go.


We Finished Spartan ULTRA 2018

We got our driver.


We Finished Spartan ULTRA 2018

Cheers Josh. So it's gonna take us about an hour or so to get there.


We Finished Spartan ULTRA 2018

5.45am I think the parking opens.


We Finished Spartan ULTRA 2018

And then 6.30am race starts.


We Finished Spartan ULTRA 2018

Let's do it!


We Finished Spartan ULTRA 2018

Morning! How are ya?


We Finished Spartan ULTRA 2018

Good thank you.


We Finished Spartan ULTRA 2018

Excellent thank you. Cheers.


We Finished Spartan ULTRA 2018

Round camp off.


We Finished Spartan ULTRA 2018

Little bit late.


We Finished Spartan ULTRA 2018

Race is supposed to start in like 10 minutes.


We Finished Spartan ULTRA 2018

As always.


We Finished Spartan ULTRA 2018

At the starting of the week.


We Finished Spartan ULTRA 2018

At summit talks you'll hear them speak.


We Finished Spartan ULTRA 2018

It's only Monday.


We Finished Spartan ULTRA 2018

Thank you. Cheers.


We Finished Spartan ULTRA 2018

Negotiations breaking down.


We Finished Spartan ULTRA 2018

This place is packed.


We Finished Spartan ULTRA 2018

I'll go with this place is packed.


We Finished Spartan ULTRA 2018

Chains of leaders start to frown.


We Finished Spartan ULTRA 2018

It's sword and gun day.


We Finished Spartan ULTRA 2018

Tomorrow never comes until it's too late.


We Finished Spartan ULTRA 2018

You could be sitting taking lunch.


We Finished Spartan ULTRA 2018

The news will hit you like a punch.


We Finished Spartan ULTRA 2018

It's only Tuesday.


We Finished Spartan ULTRA 2018

You never thought we'd go to war.


We Finished Spartan ULTRA 2018

After all the things we saw.


We Finished Spartan ULTRA 2018

It's April Fools Day.


We Finished Spartan ULTRA 2018


We Finished Spartan ULTRA 2018

We'll all go running underground.


We Finished Spartan ULTRA 2018

And we'll be listening for the sound.


We Finished Spartan ULTRA 2018

It's only Wednesday.


We Finished Spartan ULTRA 2018

Your dream does not count.


We Finished Spartan ULTRA 2018

Joe Spartans who are you?


We Finished Spartan ULTRA 2018

I am Spartans.


We Finished Spartan ULTRA 2018

Are you ready to race?


We Finished Spartan ULTRA 2018

Yeah.


We Finished Spartan ULTRA 2018

Are you ready for the ultra?


We Finished Spartan ULTRA 2018

Joe Spartans race.


We Finished Spartan ULTRA 2018

Yeah big dog.


We Finished Spartan ULTRA 2018

It's drop life.


We Finished Spartan ULTRA 2018

What did we sign up for boys?


We Finished Spartan ULTRA 2018

What did we sign up for?


We Finished Spartan ULTRA 2018

First obstacle.


We Finished Spartan ULTRA 2018

This wall is too big.


We Finished Spartan ULTRA 2018

We're hitting it.


We Finished Spartan ULTRA 2018

We're hitting it boys.


We Finished Spartan ULTRA 2018

Yeah son.


We Finished Spartan ULTRA 2018

Slappy champ.


We Finished Spartan ULTRA 2018

It's always gonna be an uphill battle.


We Finished Spartan ULTRA 2018

F*** your pathway.


We Finished Spartan ULTRA 2018

It's not over yet.


We Finished Spartan ULTRA 2018

Not a bad place to run.


We Finished Spartan ULTRA 2018

You shouldn't really practice on this kind of terrain.


We Finished Spartan ULTRA 2018

Morning.


We Finished Spartan ULTRA 2018

So young Dano has had a pack malfunction.


We Finished Spartan ULTRA 2018

His strap has been ripped off.


We Finished Spartan ULTRA 2018

So he's currently about 400m behind.


We Finished Spartan ULTRA 2018

And he's in a technical lead.


We Finished Spartan ULTRA 2018

He's trucking it.


We Finished Spartan ULTRA 2018

We've got some bells coming up.


We Finished Spartan ULTRA 2018

Oh some ropes up.


We Finished Spartan ULTRA 2018

Jesus.


We Finished Spartan ULTRA 2018

I'm gonna go.


We Finished Spartan ULTRA 2018

Easy on the shot.


We Finished Spartan ULTRA 2018

No chance in the world you reckon?


We Finished Spartan ULTRA 2018

No chance.


We Finished Spartan ULTRA 2018

I had to piss before.


We Finished Spartan ULTRA 2018

Did you piss?


We Finished Spartan ULTRA 2018

If you got it all over you.


We Finished Spartan ULTRA 2018

Yeah.


We Finished Spartan ULTRA 2018

Good on you mate.


We Finished Spartan ULTRA 2018

How was that ball mate?


We Finished Spartan ULTRA 2018

F***ing solid.


We Finished Spartan ULTRA 2018


We Finished Spartan ULTRA 2018

Solid concrete ball.


We Finished Spartan ULTRA 2018

And it's polished.


We Finished Spartan ULTRA 2018

Feels like a giant bowling ball.


We Finished Spartan ULTRA 2018

About 7.5km deep.


We Finished Spartan ULTRA 2018

So what's that?


We Finished Spartan ULTRA 2018

8km deep.


We Finished Spartan ULTRA 2018

We got the update on the watch.


We Finished Spartan ULTRA 2018

15% done.


We Finished Spartan ULTRA 2018

Loving it.


We Finished Spartan ULTRA 2018

Yeah get it Daniel.


We Finished Spartan ULTRA 2018

Burpees.


We Finished Spartan ULTRA 2018

Daniel.


We Finished Spartan ULTRA 2018

Not allowed to touch the top.


We Finished Spartan ULTRA 2018

First lot of burpees.


We Finished Spartan ULTRA 2018

I touched the bloody roof.


We Finished Spartan ULTRA 2018

30 burpees is ridiculous.


We Finished Spartan ULTRA 2018

Time to catch up to the rest of the boys.


We Finished Spartan ULTRA 2018

First water pit.


We Finished Spartan ULTRA 2018

So hard.


We Finished Spartan ULTRA 2018

I tried to save the bag but no chance.


We Finished Spartan ULTRA 2018

It's nice and cold.


We Finished Spartan ULTRA 2018

Nice and cold.


We Finished Spartan ULTRA 2018

How you doing brother?


We Finished Spartan ULTRA 2018

At least my shoes don't weigh about a quarter ton each now.


We Finished Spartan ULTRA 2018

Is that mine?


We Finished Spartan ULTRA 2018

Huh?


We Finished Spartan ULTRA 2018

Is that my one?


We Finished Spartan ULTRA 2018

No.


We Finished Spartan ULTRA 2018

Oh you got.


We Finished Spartan ULTRA 2018

Someone's got the.


We Finished Spartan ULTRA 2018

Oh you're kidding me.


We Finished Spartan ULTRA 2018

Someone took his.


We Finished Spartan ULTRA 2018

Oh my god.


We Finished Spartan ULTRA 2018

Someone took his camel back.


We Finished Spartan ULTRA 2018

We've all got black bags and when you're at an obstacle you sometimes put them down


We Finished Spartan ULTRA 2018

to complete the obstacle if you need to grip onto something or something.


We Finished Spartan ULTRA 2018

Paul blow.


We Finished Spartan ULTRA 2018

Someone's taken his and he's picked up and emptied one.


We Finished Spartan ULTRA 2018

I'm putting it through.


We Finished Spartan ULTRA 2018

I'm hitting the low water.


We Finished Spartan ULTRA 2018

Get it through.


We Finished Spartan ULTRA 2018

Last one.


We Finished Spartan ULTRA 2018

I got my bag.


We Finished Spartan ULTRA 2018

Yeah.


We Finished Spartan ULTRA 2018

I got it.


We Finished Spartan ULTRA 2018

How high have I got so far?


We Finished Spartan ULTRA 2018

So, Widget.


We Finished Spartan ULTRA 2018

How high have I got to make as much water?


We Finished Spartan ULTRA 2018

I've got sепarated blood.


We Finished Spartan ULTRA 2018

I've got s Keep talking dan forcedColl field


We Finished Spartan ULTRA 2018

ISO


We Finished Spartan ULTRA 2018

My sch 的


We Finished Spartan ULTRA 2018

That's all we got.


We Finished Spartan ULTRA 2018

How you feeling?


We Finished Spartan ULTRA 2018

Good.


We Finished Spartan ULTRA 2018

Get out of here.


We Finished Spartan ULTRA 2018

Yeah, that's it, two at a time.


We Finished Spartan ULTRA 2018

Big dogs gotta eat.


We Finished Spartan ULTRA 2018

Nice.


We Finished Spartan ULTRA 2018

Yes.


We Finished Spartan ULTRA 2018

Woo.


We Finished Spartan ULTRA 2018

Good to see you.


We Finished Spartan ULTRA 2018

That's too much.


We Finished Spartan ULTRA 2018

Nature calls, bro.


We Finished Spartan ULTRA 2018

Nature calls.


We Finished Spartan ULTRA 2018

Solo at the moment, walking up this hill.


We Finished Spartan ULTRA 2018

You can hear the music in the background,


We Finished Spartan ULTRA 2018

but it's kind of peaceful up here.


We Finished Spartan ULTRA 2018

This is a massive hill.


We Finished Spartan ULTRA 2018

We've been walking up it for a solid 10 to 15 minutes.


We Finished Spartan ULTRA 2018

I don't know where the other two boys are at the moment,


We Finished Spartan ULTRA 2018

but that's all right.


We Finished Spartan ULTRA 2018

Then the competition's against yourself.


We Finished Spartan ULTRA 2018

I don't know how far we're in.


We Finished Spartan ULTRA 2018

Probably close to halfway, loving it.


We Finished Spartan ULTRA 2018

The water is a good break up.


We Finished Spartan ULTRA 2018

Cools down the body.


We Finished Spartan ULTRA 2018

Had two gels, half a bar,


We Finished Spartan ULTRA 2018

probably half of my water tank.


We Finished Spartan ULTRA 2018

And don't know what the game plan is, just keep going.


We Finished Spartan ULTRA 2018

To me, it's just binary.


We Finished Spartan ULTRA 2018

Just start and finish.


We Finished Spartan ULTRA 2018

That's it.


We Finished Spartan ULTRA 2018

Just keep running, keep moving.


We Finished Spartan ULTRA 2018

That's what we're gonna do.


We Finished Spartan ULTRA 2018

Just not gonna stop, simple as that.


We Finished Spartan ULTRA 2018

How long?


We Finished Spartan ULTRA 2018

Three hours and 30.


We Finished Spartan ULTRA 2018

Oh, sweet.


We Finished Spartan ULTRA 2018

That was easily the hardest one so far.


We Finished Spartan ULTRA 2018

Yeah, it does.


We Finished Spartan ULTRA 2018

Fuckin' jeez.


We Finished Spartan ULTRA 2018

Just did a sandbag carry.


We Finished Spartan ULTRA 2018

60 pounds sandbag, whatever that is,


We Finished Spartan ULTRA 2018

like 30 or so kilos up a hill like this.


We Finished Spartan ULTRA 2018

There's no good way to carry a sandbag.


We Finished Spartan ULTRA 2018

I just did it across my shoulders.


We Finished Spartan ULTRA 2018

About 20 k's deep.


We Finished Spartan ULTRA 2018

Gonna have to do that again in about three hours or so.


We Finished Spartan ULTRA 2018

Four hours, yay.


We Finished Spartan ULTRA 2018

This one's just made to break you.


We Finished Spartan ULTRA 2018

You gotta fill up your own bucket.


We Finished Spartan ULTRA 2018

It's like filling your own grave.


We Finished Spartan ULTRA 2018

Grab your bucket, go to the top hole,


We Finished Spartan ULTRA 2018

take a full walk down in front of you.


We Finished Spartan ULTRA 2018

You gotta fill this thing with that.


We Finished Spartan ULTRA 2018

Go, Berkey.


We Finished Spartan ULTRA 2018

Get it, Berk.


We Finished Spartan ULTRA 2018

You got it, mate?


We Finished Spartan ULTRA 2018

You gotta just stick it under the wall right there.


We Finished Spartan ULTRA 2018

Yes.


We Finished Spartan ULTRA 2018

Nice, mate.


We Finished Spartan ULTRA 2018

You got this, fella.


We Finished Spartan ULTRA 2018

Fill it.


We Finished Spartan ULTRA 2018

Go on, Scotty.


We Finished Spartan ULTRA 2018

Killin' it, bro.


We Finished Spartan ULTRA 2018

It's killin' me.


We Finished Spartan ULTRA 2018

I hope you got a bet riding on that.


We Finished Spartan ULTRA 2018

Thanks, mate.


We Finished Spartan ULTRA 2018

Enjoy.


We Finished Spartan ULTRA 2018

Officially the hardest.


We Finished Spartan ULTRA 2018

The hardest one yet.


We Finished Spartan ULTRA 2018

Burpees from all the way down here


We Finished Spartan ULTRA 2018

with a sandbag to here.


We Finished Spartan ULTRA 2018

Halfway.


We Finished Spartan ULTRA 2018

Yeah.


We Finished Spartan ULTRA 2018

Halfway, brother.


We Finished Spartan ULTRA 2018

Second lap, cuz.


We Finished Spartan ULTRA 2018

Easy money.


We Finished Spartan ULTRA 2018

Got the head torch this time.


We Finished Spartan ULTRA 2018

Stocked up.


We Finished Spartan ULTRA 2018

Probably had a bit too much fluid,


We Finished Spartan ULTRA 2018

but we'll get there.


We Finished Spartan ULTRA 2018

Not as many people here on the second lap, bro.


We Finished Spartan ULTRA 2018

This is exactly at the start of the race


We Finished Spartan ULTRA 2018

where we had that massive traffic jam.


We Finished Spartan ULTRA 2018

What are you used to?


We Finished Spartan ULTRA 2018

I'm used to it.


We Finished Spartan ULTRA 2018

It's getting hard, man.


We Finished Spartan ULTRA 2018

That's true.


We Finished Spartan ULTRA 2018

Wow.


We Finished Spartan ULTRA 2018

Sorry.


We Finished Spartan ULTRA 2018

Oh, that is sweet.


We Finished Spartan ULTRA 2018

Yeah, come on.


We Finished Spartan ULTRA 2018

Lay down now.


We Finished Spartan ULTRA 2018

Lay down.


We Finished Spartan ULTRA 2018

Now.


We Finished Spartan ULTRA 2018

Rosie, so now I don't know where your boys are right now,


We Finished Spartan ULTRA 2018

but just wanted to let you know


We Finished Spartan ULTRA 2018

your boys are thinking of your brothers.


We Finished Spartan ULTRA 2018

Spartans.


We Finished Spartan ULTRA 2018

We also want to let you know


We Finished Spartan ULTRA 2018

your boys about to finish the Spartan Ultra.


We Finished Spartan ULTRA 2018

Oh.


We Finished Spartan ULTRA 2018

Two to go.


We Finished Spartan ULTRA 2018

Lip wall and ropes.


We Finished Spartan ULTRA 2018

Well done.


We Finished Spartan ULTRA 2018

You hear this jingling?


We Finished Spartan ULTRA 2018

So you're going to hear soon.


We Finished Spartan ULTRA 2018

Get up.


We Finished Spartan ULTRA 2018

Second last one.


We Finished Spartan ULTRA 2018

Pulling easy, easy.


We Finished Spartan ULTRA 2018

Easy, bro.


We Finished Spartan ULTRA 2018

One more, one more.


We Finished Spartan ULTRA 2018

One more and you're done.


We Finished Spartan ULTRA 2018

Hit the bell, bro.


We Finished Spartan ULTRA 2018

Hit the bell.


We Finished Spartan ULTRA 2018

Yeah.


We Finished Spartan ULTRA 2018

That's it, brother.


We Finished Spartan ULTRA 2018

Jump off.


We Finished Spartan ULTRA 2018

We finished, bro.


We Finished Spartan ULTRA 2018


We Finished Spartan ULTRA 2018

No, he's Ultra.


We Finished Spartan ULTRA 2018

Good job.


We Finished Spartan ULTRA 2018

Come get your shirt, bro.


We Finished Spartan ULTRA 2018

Well done, boys.


We Finished Spartan ULTRA 2018

Well done.


We Finished Spartan ULTRA 2018

I'm done.


We Finished Spartan ULTRA 2018

Thank you.


We Finished Spartan ULTRA 2018

I got medium.


We Finished Spartan ULTRA 2018

Made it home.


We Finished Spartan ULTRA 2018

Just arrived.


We Finished Spartan ULTRA 2018

Can barely walk.


We Finished Spartan ULTRA 2018

50KM's done.


We Finished Spartan ULTRA 2018

My boys and I was a guardian angel.


We Finished Spartan ULTRA 2018

He's off.


We Finished Spartan ULTRA 2018

Do you want it?


We Finished Spartan ULTRA 2018

Yeah, better.


We Finished Spartan ULTRA 2018

See you, coach.


We Finished Spartan ULTRA 2018

How long, how much did you get cut off by, bro?


We Finished Spartan ULTRA 2018

56 seconds.


We Finished Spartan ULTRA 2018

So the first lap, some 25KM or something course, my boy has a five-hour cut off, came in at five, five hours, 56 seconds, and then couldn't finish the rest of the race.


We Finished Spartan ULTRA 2018

What did the guy say?


We Finished Spartan ULTRA 2018

He said it was too late.


We Finished Spartan ULTRA 2018

I missed a cut off.


We Finished Spartan ULTRA 2018

Yeah.


We Finished Spartan ULTRA 2018

We're way too buckled to tell you about obstacles and whatnot now, but we'll do that, I think, throughout this video or something.


We Finished Spartan ULTRA 2018

I'm not sure exactly how it's going to play out, but how'd you find it, brother?


We Finished Spartan ULTRA 2018

Mate, it was really well organized.


We Finished Spartan ULTRA 2018

I'm buckled.


We Finished Spartan ULTRA 2018

That's why I'm sitting down in this interview.


We Finished Spartan ULTRA 2018

Just like to give those traditional shout outs.


We Finished Spartan ULTRA 2018

I actually can't stand up right now.


We Finished Spartan ULTRA 2018

I'm going to go get a feet transplant and some food.


We Finished Spartan ULTRA 2018

You keen?


We Finished Spartan ULTRA 2018

Good job, boys.


We Finished Spartan ULTRA 2018

We did it.


We Finished Spartan ULTRA 2018

Spartan Ultra, you were there, mate.


We Finished Spartan ULTRA 2018

You were there.


We Finished Spartan ULTRA 2018

I'm an angel.


We Finished Spartan ULTRA 2018

One last aru.


We Finished Spartan ULTRA 2018

Lettabop.


We Finished Spartan ULTRA 2018


Early Morning Animal Style Park Workout (bodyweight only)

6 a.m. a little bit of rain never hurt no one


now the fun little part about getting this the ring set up is getting them


through the beam so we're setting them up a little bit undercover today because


it might rain so I got this one first go let's see if we can do the same for the


second one


oh


now


come on now now


okay so we're getting some little bit of warm-up in this get active standard


stuff so what we're doing here moving around because again we want to get the


hips moving and because we're going to be doing a lot of groundwork we get those


wrists warmed up and Devo don't copy what Devo is doing


this is great for a in a groin activation so we're keeping it simple


today getting the wrists warmed up we're gonna do some rings we're gonna do some push and


pull my elbows a little bit sore from jiu-jitsu training not thanks to you and


then we'll go over to the grass patch and do some animal movements so because


we're going to be using our hands a lot that's why you want your wrist to be


nice and warm nice and ready you ready Ashnim? Any words of inspiration for today?


You're living up to your motto of ah hey guys I'm Cameo Dave every now and then you


might see me participate in something other than not


each time hey guys I'm Cameo Dave you too can look like me you eat great and


exercise in just three seconds I can show you what your body can achieve


from this to this


nice outfit man, hey man nice outfit you look great yeah alright double D coming at ya


getting into it yeah no chance a rainy day was gonna stop us so we came down to


the waterfront some nice and easy movements again my elbow is a little bit


sore at the moment so we were doing ring push-ups instead of ring dips we did


five sets of ten reps each of these Dave just love a laugh


so as you come down on my... ready? keep going you're doing a good job man


thanks to you do it chase that b-roll you can do it


oh I got this thanks Dave I love you man I'm waiting for the fist punch


if you're working out get yourself Cameo Dave office unlimited encouragement


now of course if you can't do the ring push-ups you can always substitute it


with normal push-ups after the ring push-ups we then moved on to ring pulls


so we're just getting the pushing and the pulling movement in the same session


again with the ring pulls we did five sets of ten reps each the idea is here


just to let your body hang pull it up to as far as you can go and go back down


you ever seen Avatar? so there was a yoga class just here before but because it's


a little bit drizzly it's freed up so Dave and I have a jiu-jitsu competition


in two weeks look at him I wouldn't fight him would you fight him? so basically we


got the formalities done with the rings just some simple pushing and pulling


exercises five by ten each now we're gonna do some groundwork which is aka


animal flow there's no real routine to this so one of the things I'm trying to


do for this year or actually going forward with most workouts is keeping


none of them the same so just mixing it up every single time ready Archnem?


we'll probably start off let's start off with some stick game so this is a


variation of stick game I'm gonna drop it and Dave has to pick it up you pick


it up then I have to pick it up. and you pick it up when I'm put down? yeah we call this


pick up what you put down and whoever drops it first is out


oh that's one to me first to three


oh two all the decider yeah listen to Dave after I claim victory in the stick game we then moved


on to the groundwork so we're keeping it as I said keeping these workouts nice


and fun we started with the rings which is what I like to call the formalities


and then we got on the ground which is kind of just unstructured work here the


first was bear crawl so essentially just crawling on the ground for 20 or so


meters then we moved into side hop and each of these exercises you see here


that we're doing on the ground we did for at least two rounds the side hop


here is you crouch down put your hands on the ground hop to the left for one


set and then hop to the right for the next set after the side hop we moved on


to kick sits and this is what you see here is we're doing a little kick


through and then sit down kick through sit down you see Dave sort of stays


vertical here the ideal position is to keep both hands on the ground kick one


foot through and then sit your thigh on the ground nice and slow after kick sits


we moved on to some frog hops now you could jump here but we decided to this


is actually more of a gorilla call than a frog hop but we'll call them frog hops


finally we finished up with the ground version of stick game now the idea here


is that the person with the stick has to maneuver it around the person on the


ground whilst the person on the ground keeps as many limbs on the ground as


possible far out there was a mouthful but as you can see here I'm just jumping


around Dave and he's trying to move around the stick and now you swap over


when the person on the ground gets tapped with the stick due to fatigue


how was that mate excellent debrief oh look at that grassy hands there's a


storm a brewing go ahead there far out not your typical sunny morning we kept


that one nice and simple did some start off on the rings and then just some


some ground-based movements because what do we have coming up in two weeks night


comp coming up in a couple of weeks all the boys just about getting amongst it


jujitsu competition yep that was a good combination of ah you know the getting a


bit of a pump as well as get some cardio it's a really good movie going yeah


that's a good all-around session I'm not too tired I'm not as fit as this guy so


probably you're still moving probably probably more relatable to a lot of you


guys and that was definitely doable yeah no matter no matter how you are so the


whole premise here is just basically you don't you don't always need all the


equipment right you can get out just use a patch of grass use your body weight


use gravity the closer you are to the ground the more of a challenge it's


going to be right so have some fun bring your arch nemesis along if you can and


spend a little time dancing about we go get shelled off so we're not a pit of


itchiness yeah it's gonna happen I didn't take my


How to check if a neural network has learned a specific phenomenon?

Hello everyone! I will kick off my YouTube series about Explained AI Methods and Papers


with the question, how do we check if a neural network has learned to solve task A?


Well, the answer for this question is not so interesting. Since we have trained the


neural network for solving A, we have training data for A. Then we test how well the network


solves A on the held out test data. And we are done.


No, come on, let us ask something more interesting. How do we check if a neural network trained


on task A has learned a phenomenon specific to task B? And we will give the answer focusing


on NLP, but it is generalizable to many other applications like computer vision.


Since the AI field is changing so rapidly, this video is a snapshot of the current state


of research. Simultaneously, it is my attempt to explain intriguing and sometimes complicated


concepts that researchers use every day in a simple and understandable manner.


So let's get back to the original question. How do we check if a neural network trained


on task A has learned a phenomenon specific to task B? We start here with a neural network


and supposing it was trained on large amounts of training data like on Wikipedia, where


it reads the text and has to predict masked words. Can a neural network read? This masked


word prediction is our task A. Because predicting masked words by a neural network has been


lately proven to be extremely effective on many other tasks apparently unrelated to masked


word prediction, we want to test this. Is it true that if the neural network trained


to complete missing parts of text has also captured interesting linguistic phenomena?


And before we can answer this question, we have to choose one phenomenon we want to probe


for. Checking if and how much a neural network trained on task A captures a specific linguistic


phenomenon is referred to by terms like probing or diagnostic classifier or probing task B.


So the task B comprises the linguistic phenomenon we want to test for here. Keeping it simple


now, I will use the example of sentiment expressed in text, where the text is no longer than


a paragraph. And here the neural network has to tell us if a paragraph expresses positive


sentiment or negative sentiment. The example could be anything else, from the grammaticality


of a sentence to natural language inference. Now, back again to our original question how


do we check if a neural network trained on task A has learned a phenomenon specific to


task B, we wonder how do researchers try to answer this question? Well, with probing.


Okay, okay, and how do we probe? We take the network as is, trained on task A, and remove


the last part, the one that was responsible for mapping all the weights encoding patterns


in the data for making the final prediction. Now, to test if this part can also do sentiment


classification, we then replace the last layers with another fresh classifier that has not


yet been trained to do anything. It cannot map the original parameters of the network


to sentiment classification. Okay, then let's train it to. In order to keep everything preserved


that we have trained from task A, we freeze, so leave unchanged, the old part of the network


and this fresh part we train. And we train it on a relatively small data set of sentiment


classification, our task B, containing paragraphs labeled with positive or negative sentiment.


And in this scenario the new classifier, our probe, is performing binary classification


where the output is either 0 for negative sentiment or 1 for positive sentiment. From


the way the probe trains, we differentiate between the following scenarios. If the classifier


trained on the small data set for probing is learning fast and performing well, then


the weights we left unchanged have been already capturing the information of the probe task.


In the second, worse scenario, if the classifier trained on this small data set is not learning


anything and is barely performing better than when it is untrained, then the weights of


the big neural network have been not capturing any information about the probing task at


all, or so it seems. Okay, now, if we would ignore the most recent research, we would


stop here. And if you clicked on this video for getting the answer to the original question


of how do we check if a neural network has learned something in NLP, then you are ready


to go, since we explained how it works on the example of sentiment analysis. And the


same procedure holds for many other phenomena and is not even restricted to NLP.


Now in the following, I will be addressing the contribution of a recent paper where they


address following problems. Neural networks in general tend to overfit, meaning that they


specialize on a certain task, memorizing input and output. And this problem gets even bigger


where the size of our training set is small, and this is usually the case for our probing


task B. Overfitting happens with our probing classifier, where it is able to learn the


new probing task, but is also able to learn a completely random probing task, where the


labels have been randomly altered. Also, sometimes the expected difference between an untrained


probe and a trained one is not as big as expected. Can the authors do something to save the standard


probing from its problems? Oh yes, they do! They use an information theoretic view. And


since this might sound intimidating, the idea is elegant and yet so simple. Additionally


to measuring how many times the neural network with the trained probe can give right or wrong


answers, they check if the neural network can also efficiently transmit the data. This


means if we call our neural network Bob and the probing classifier Alice, Alice is then


the person receiving the answers of Bob and mapping them to labels. And Bob sees some


data, processes it through the neural network and sends its output to Alice. So Alice receives


a message, tries to decode it and reconstruct the right label and gives him credit if she


could decode the right label from Bob's message. But instead of measuring only the capability


of Bob and Alice cooperatively getting to the right answer, we are now additionally


measuring how well Bob could send the message in a short, compressed form, for which we


would assume he had to understand more and see patterns in this world. So if you liked


this information theoretic approach and you want to know more, read the paper. It is so


well written that it is really a pleasure to read. I have linked it in the description


of the video below. Thanks for watching, do not forget to like and subscribe and see you


Movement is medicine | 10-minute Bodyweight Bedroom Workout (follow along)

Welcome back everyone to episode 2 of reps for Rona and because we're all on lockdown at the moment


Or if you're not you kind of should be stay home if you can to reduce the spread of this virus


I figured it'd be a good idea over the next few weeks to basically post one of these 10 minute videos every day


So we can work out together stay indoors stay active stay moving


So on this episode we have five exercises


Actually, that's a lie. We've got one exercise and it's the warm-up mixed with


The other exercises and it's just 10 minutes of elaborate dance. So join in that's what we're gonna do now


I'm kidding, but that's a good warm-up. We have shoulder taps


staggered squats hollow hold


stationary crab and Cobra push-ups


Alrighty


We're gonna start we've got 10 minutes 30 seconds on 30 seconds off


Beautiful first one shoulder taps down on the ground tap shoulder tap shoulder


Remember we're not going for pace here. We just want to get through the movements 30 seconds of moving


That's it


Keep it up


tap each of your shoulders


Nice


Keep going


There we go. Oh


Beautiful one down. So we've got five exercises. We're gonna go through them for two rounds


30 seconds on 30 seconds off total up 10 minutes. So we've done one of shoulder taps


The next thing we have is staggered squats


Now we're going to start with the right foot forward and then move to the left foot forward in the second round. So


Where we start a staggered squat is just like this one foot forward one foot back


So I'm gonna go like this


And then just down and up 30 seconds


You're struggling to find balance go a little bit slower


If you can't find balance at all, you can do double leg squats, but I'm gonna be doing staggered squats if you can do these


Do these


So I do Brazilian jiu-jitsu and this is a great a great sort of technique to practice


When you're trying to get down and lunge towards someone in a wrestling technique to take them down


Wonderful, so even I was losing a bit of balance there


Alright staggered squats are done now we have hollow hold now this is


Kind of gonna work similar similar sort of muscle region as a plank, but you do it on your back


So we'll start out like this


lying flat on the ground


Arms fully extended legs fully extended what we're gonna do


Is lift our arms and legs off the ground


While sucking our belly button in to our spine


We're just gonna hold it here


You want to breathe nice and deep breathe right into your belly button


Try and pull that belly button against your spine


The further you extend out your arms and legs the harder it gets


Beautiful now up and off the ground


That's another one for maybe next time we can just spend 30 seconds getting up and off the ground


So we've done hollow holds


And now we're going to do


Stationary crab well this this exercise might have a different name


But it's the best one I could actually think of and once you see it you kind of realize that


It's sort of like a stationary crab if it's if you got a better name for it. Let me know


So we're gonna start on all fours


Reversed and bring one leg forward one arm over and then one leg under


One arm over remember it's opposite arm opposite leg


We're going this way


Then right leg left arm


left leg right arm


right leg left arm


Left leg right arm


I'm even confusing myself here


The point there is just to do it


Okay, I'm not actually sure what this is tabletop. We'll call it tabletop, and then just make sure you're moving


Changing arms changing legs, but we're supposed to be resting for that


So wonderful with four through the next one is


Cobra push-ups now if you ever in doubt of trying to


I'm not sure what movements you could do


Just think of nature how do animals move now this isn't really how a cobra moves, but I got told these are cobra push-ups


And so I'm calling them cobra push-ups, and we're going down across right up


down across right up


down right left up


down left right up


up


Beautiful


Pop up to the top


Okay, so we've been one round through


How good is that so we're back to shoulder taps?


By the way while while you're here


I'm reading a great book food fix if you're looking for something to read while you're locked indoors


This is an amazing book on how the food system is basically fucked


so


I'm educating myself on that as a proponent of health oh


We'll continue that the next rest we've got shoulder taps shoulder taps left


Right again nice and slow here the goal of these reps for Rona sessions is not to exhaust ourselves


But just to get up get a little bit of blood flow happening get moving


get active


boost that immune system


Immune system


Immune immune system there we go


Wonderful


Where were we yeah as a proponent of health


especially first principles health that's


movement sleep food


They're probably the three three pillars of health and it all comes back to if you if you have a bad diet


No amount of movement no amount of reps for Rona


Are going to to help fix your health issues so in order to fix the food system?


I need to educate myself more about it alright. We are to staggered squats this time left foot forward


Down this is almost like a like a lunge here, but that's what we're focused on doing go straight ahead


Just down and up


Right foot back left foot forward


That's it


Keep going


Keep going we're doing this reps for Rona


Keeping our immune system high so we can beat this disease and we will beat this disease


Beautiful


staggered squats done to hollow hold


We're up to hollow hold I actually find hollow hold quite difficult


It's showing me I need to work on my core you could even what we might do is a reverse hollow hold so


Same sort of movement we did before with the hollow hold remember our arms and legs extended


But this time instead of lying on our backs will lie on our stomach, so let's get set up down on the ground


Extended arms extended legs there we go almost like you're a banana. That's it


Channel your inner banana


How you keeping yourself entertained or what are you doing when you're locked up at home


This is how I entertain myself by dancing


There we go beautiful


We know a lot of reading


Got a stack of books. I'm gonna go through check out those books


What are you reading at the moment?


I'm reading food fix. I'm also reading


Notes from the underground by how do you say that Dostoevsky Dostoevsky


Great great book


Oh in the side ourselves, what do we got we're finishing it off Kovach push-ups on a stationary crab


That's it


It might even reverse this one so reverse


But all we're doing here is you're swapping our opposite arms and opposite leg


in a circular motion


heads


We are stationary crabs mix it up if you want


Varieties of spice of life right


We'll spend this rest session doing a little dancing so shake it out


Because we've only got one more left


We got Cobra push-ups


If you have any suggestions of exercise you'd like to to see in this reps for Rona session leave a comment below


What body weight exercises are your favorite? We might might try that in one of the next videos because as I said


Make one of these for the next few weeks


Cobra push-ups, let's finish this off 30 seconds down right left up


Down right left up


down right left up


Up down right lift up. We've gone right too much. Let's go left


right up


Down left right up


There is 10 exercises now this is gonna go off in a second we might


Just can that


But workout pause beautiful. That's a great little simple timer app isn't it?


Tabata on the App Store. I believe it's called if you want to try this out yourself


So that was 10 simple exercises. We had shoulder taps staggered squats left and right feet


hollow hold stationary crab and


Cobra push-ups and it just not goal here is not to overexert ourselves


it's just to work up a little bit of blood pump have a little bit of fun while doing it and


Get ourselves moving if we've been spending too much time stationary at this office chair like like I do during the day


but wherever you are in the world, I hope you stay safe. Hope you stay alert and


Please leave a comment below if you'd like to see anything else in the future video


Otherwise keep moving and don't forget if you happy and you know it wash your hands


Building a machine learning app | 10 hour coding livestream

We're on team.


Boom. We're on.


Going live.


Yeah, yeah, yeah, yeah.


Okay, maybe I start with just my face.


There we go. Okay, we're in.


If you're in the chat, let me know if you can see me, let me know if you can hear me.


Because we have a very exciting stream today.


We're celebrating 100,000 subscribers, which is an insane amount.


Yo, yo, yo.


Let me know if you can hear, see, all good.


Hello, everyone. Welcome, welcome, welcome.


I like your t-shirt. Thank you, Oscar.


Perfect sound.


Beautiful, beautiful, beautiful.


And what about the screen?


If I put the screen on here, let's get some code.


Can you see this all right?


Because we're going to be going for 10 hours and I would hate for people not to be able to see.


So let me know if you can see what's happening.


Sound like a fellow Aussie.


Yes, yes, yes.


Movember mustache.


I do have a Movember mustache.


We can hear and see very quick, clearly.


Amazing.


Okay, from me, YouTube is looking good.


Let's get started.


First, what we're going to do is


we need to lay out some ground rules for the stream.


So welcome, everyone.


I have no idea how this is going to turn out.


10 hours is a long time, but not really because it's only really just a day.


So let's go over here and we will get page title is it's November the 6th where I live.


It is 8am in the beautiful northern beaches of Brisbane.


So I can't show you it, but I have beautiful water there.


You can see the trees, the water, the sky.


It's good. It's a good day.


November 6th, 100k live stream celebration.


The editor is a bit small.


I'll increase that.


Okay, so what about this?


How's the size there?


Is that a good size for the editor?


It's afternoon in the real world.


11pm in France.


Hello, everyone.


Everyone leave their country flag in the chat.


Let's see how many different countries we have.


Okay, so that's that's good.


That's where we're going to go.


Okay, and now let's go here.


How do I zoom in?


Zoom in.


Zoom. We're just going to use Notion actually.


Notion.


Add to that way you guys can see what's going on as well.


November 6, 100k live stream celebration.


Look at that. I can't even zoom in.


Open as page. We're on.


Okay, so let's add a little icon.


We can go party.


Okay, you can all see this.


Here's what we're going to do today.


So we need to lay out some rules.


We've got plenty of time.


So we're not in a rush. Rules.


So every hour equals 10 push-ups, 10 sit-ups, no 10 squats.


And let's go 10 kicks, 10 punches.


That way we got to keep moving.


All right, and then let's go surprises at 77 minutes in and then that's about it for the timing wise.


So let's set a timer.


There's going to be a surprise at 77 minutes in. Everyone.


We're going to set a timer.


Timer 77 minutes.


Oh 77 minutes and 77 seconds.


Let's do that.


Okay, so there's surprises when this timer goes off.


That way every hour if we keep moving because we don't want to I don't want to be inside and sitting down for 10 straight hours.


That's not me. You know, that's not me.


And then what we're going to build.


So let's build a full stack ML application and we're going to build I had this idea something simple because 10 hours is a lot of time.


But it's also not enough time if something goes wrong because I'm going to be doing all of this live.


So let's build food not food dot app.


So who remembers hot dog not hot dog.


We'll start off and again if this takes less than 10 hours, we can do something else.


But hot dog not hot dog.


Of course, the model to build for this is pretty straightforward.


You get photos of hot dogs and not hot dogs, but we want this deployed.


So I want to before the end of the stream.


You should be able to go to food not food dot app and use a machine learning model to take a photo of something and see if it's food.


So what we have to do is let's go to do we need a data set.


We're going to do all of this from scratch scratch collect data set and then we're going to model data set build application deploy application.


And then after that, well, who knows?


Okay, so we don't have any data.


We don't have a model.


We don't have an application and we can't we haven't deployed the application yet.


So let's start a GitHub repo.


Who's in for that?


We'll build food not food dot app and then if we have more time we can of course do whatever but we need to build a full stack application today.


And let's go new repo.


We want what should we call it food not food.


Machine learning powered app to decide whether a photo is food or not.


Who wants to build this choose a license.


It's going to be all open source so you can copy it and whatever but we have to collect the data set get ignore and let's make it python.


Create repo.


So there's the repo.


Mr.


D Burke food not food.


Hello RJ Nirmala.


Oh, look at all these flags.


Thank you so much for sharing them.


We have UK we have America.


We have India.


We have Netherlands another America beautiful.


We have Poland.


Thank you all so much.


We have a pirate flag beautiful.


If you're living if you're watching this from a pirate ship. Hello.


It's going to be some treasures out there.


I am from Australia.


So let's do it.


Okay, we need a data set people who's ready to start going.


So I'm going to also probably put the notion here.


That way you can see.


Copy link.


Show link options people want that way people can.


See notes on notion.


Okay, everyone's ready to go now food not food.


And we also need an image.


Save image as.


Hot dog not hot dog.


Poland.


Hello.


Oh the kangaroo.


Egypt Pakistan France, Nigeria.


Hello everyone.


Welcome.


This is going to be fun.


All right, we're going to spend most of it coding and then if we have spare time, I'll answer questions.


Probably by the time I get cooked.


I'll I'll just start talking to you for a bit and then go back to coding.


I actually don't know.


I have no idea how this is going to turn out.


So we'll see.


We're doing it to celebrate a hundred thousand subscribers.


So thank you so much.


Wherever you are in the world for tuning into my crazy videos.


This will probably be one of the craziest.


So let's go to CD food not food.


LS clear beautiful food not food.


Okay, I'm going to now add the image into there.


So LS desktop.


Tell me if you can see the terminal.


We're going to be using this a lot.


Clear LS.


We want hot dog not hot dog.


Move.


I want code food not food.


Now we're going to add hot dog not hot dog.


So people know what we're working on.


First commit add hot dog image.


What we're going to build.


So let's let's do this collect data set.


So I want to show you how we can this is.


We're going to deploy it a few different ways.


Actually, I just realized this.


So a lot of people ask me how do I work on my full stack application?


So hopefully this stream is going to show you like how I would approach it.


So we can do it with Gradio.


We can also do it with live web app.


We could do it as an API.


I mean, there's three different ways, but I'm probably going to use it with


TensorFlow.js.


Why is that?


Because TensorFlow.js runs in the browser and it's very easy to to once you


if you know a bit of JavaScript, you can get it up and running pretty quickly.


So collect data set.


We need need images of food and not food.


We're going to figure that out, right?


We don't have a data set and then we'll go model data set.


We want to build a computer vision model to classify food and not food.


And oh, I just remembered that we want I've got a tweet here.


This is the important thing about data sets.


We go here.


You all know Abraham loss function.


Very very smart person.


This is why we have to build a data set.


So we want data set or no, we're going to ML model.


Why isn't that embedding?


It won't embed.


That's right.


This very important.


If you had eight hours to build a machine learning model, we have 10.


I'd spend the first six hours preparing my data set quote from Abraham


loss function, which is of course Abraham Lincoln, but I've named that.


So let's bring this in here.


This is what we got to pay attention to.


What if you it's easy to start a machine learning model with a data set,


but what if you don't have a data set and what we're going to build?


What we're going to build and we want let's get in that image of hot dog,


not hot dog.


Choose image.


Red hot dog, not hot dog.


Code.


Caption.


What we're building except for food, not food.


A nice and simple app.


That's what we want.


So full stack machine learning application surprises at 77 minutes in every hour.


Someone keep a track of an hour and thank you for.


This is going to be saved.


Yes, you're right.


You're good in JS.


Is it easy to me to learn machine learning in JS?


Yes, of course it is.


I'm about to show you.


I'm terrible in JS, but we're going to figure this out.


Tweet.


Thank you.


There we go.


So now let's go back to where we were going to get out of that.


Put in the GitHub.


What we're building.


Except for food, not food.


Let's go image source equals.


Did that not push?


Okay, we're on.