fabiochiu/medium-articles huggingface dataset:
Run the Dishwasher Twice
By: Kate Scott
Tags: Mental Health, Self, Home, Life Lessons, Therapy

Run the Dishwasher Twice

A lesson on throwing out the rule book and saving yourself

Photo: Leren Lu/Getty Images

When I was at one of my lowest points in life, I couldn’t get out of bed on some days. I had no energy or motivation and was barely getting by.

Even therapy seemed like too much effort. I had been going every week, and on one particular day, I didn’t have much to “bring” to the session. My therapist asked how my week was going, and I really had nothing to say.

“What are you struggling with?” he asked.

I gestured around me and said, “I dunno, man. Life.”

Not satisfied with my answer, he said, “No, what exactly are you worried about right now? What feels overwhelming? When you go home today, what issue will be staring at you?”

I wanted to give him an answer that was substantial, something that seemed worthy of struggle. But instead, I told him the truth.

“Honestly?” I said. “The dishes. It’s stupid, I know, but the more I look at them, the more I can’t do them because I’ll have to scrub them before I put them in the dishwasher, because my dishwasher sucks, and I just can’t stand to scrub the dishes.”

I felt like an idiot just saying it out loud. What kind of grown-ass adult is undone by a stack of dishes? There are people out there with actual problems, and I’m whining to my therapist about a basic household chore?

And yet my therapist nodded in understanding. And then he shared his advice:

“Run the dishwasher twice.”

Huh? I began to tell him you’re not supposed to do that, but he immediately stopped me.

“Why the hell aren’t you supposed to? If you don’t want to scrub the dishes and your dishwasher sucks, run it twice. Run it three times, who cares?! Rules do not exist.”

His words blew my mind in a way that I don’t think I can properly express.

That day, I went home and tossed my smelly dishes haphazardly into the dishwasher and ran it three times. I felt like I had conquered a dragon.

The next day, I took a shower lying down.

A few days later, I folded my laundry and put my clothes wherever the fuck they fit. As I reveled in my newfound freedom, I stopped seeing each day as a series of arbitrary rules to follow. Eventually, I felt free enough to set goals again, on my own terms.

Now that I’m in a much healthier place, I rinse off my dishes and place them in the dishwasher properly. I shower standing up. I sort my laundry.

But at a time when living was a struggle instead of a blessing, I learned an incredibly important lesson:

There are no rules.

Run the dishwasher twice.
Handwritten digit classifier — Your first end to end CNN in 5 minutes
By: Vidisha Jitani
Tags: Machine Learning, Neural Networks, Artificial Intelligence, Deep Learning, Data Science

Digit classifier is apparently the new Hello World!

Yes, this is the most basic Convolutional Neural Network example. Therefore understanding this one is of prime importance. So, whenever we start something new, running our first hello world program might seem easy but has a lot of friction attached to it. Running it successfully can sometimes take days — primarily because of the setup involved, getting caught in bugs which looks like alien text to us, etc.

So, my main motivation behind writing this article is to help you in removing this friction — so that you can run your first-ever program on CNN in just 5 minutes.

Pre-requisites

Should know the basics of CNN. I would highly advise to do a google search and understand the convolution layer and max-pooling layer. You should have a good understanding of the maths behind it. I would highly recommend going through my previous article for this. Run this program via Google Colab.

Did someone just run their first CNN programme?! Congratulations 🎉

How did it feel?! If you haven’t run it yet, I would highly recommend doing so. Google Colab is very simple to use software which removes all the unnecessary need of doing the setup on our machine. Highly recommended if you are still learning Deep learning. Now, let’s break it down and understand each and every component.
8 Great Ideas for Programming Projects That People Will Use
By: Filipe Silva
Tags: Programming, Startup, Software Development, Inspiration, JavaScript

8 Great Ideas for Programming Projects That People Will Use

Make a big difference with a little software

Photo by Simon Abrams on Unsplash

Two trends are becoming increasingly apparent in the software development world.

It is becoming easier by the day to build a software product.

The number of people in search of ideas for those software products is increasing.

With the advent of no-code solutions and the hacker/maker movement, we, more than ever, are recognizing the power of being able to idealize, build, and ship a product that can impact more people than ever in history.

Having a CS degree or knowing a programming language is becoming less of a factor in what you can accomplish with software, so it’s only natural that more people want to try their hand in building something with these technologies. Since you’re at it, why not consider a solution for somebody else’s problems?

When I published the 12 Great Ideas for Programming Projects That People Will Use article, I became even more convinced that people were clamoring for this type of quick start.

The feedback I received was incredible, and I knew I had to find another batch of ideas at least as good as the ones in that article.

The search is over and here they are.

Note: The illustrations in this article are free at manypixels.
AAG Annual Meeting 2018 Conference Memo
By: Toshikazu Seto
Tags: Conference, Geography, Artificial Intelligence

Lecturer of CSIS at the University of Tokyo / Social Geography / Participatory GIS / Neogeography / Volunteered Geographic Information / Qualitative GIS

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America’s Boldfaced Serial Killers
By: Charlie Kufs
Tags: Metaphor, Random Terrabytes, Analogy, Serial Killers, Coronavirus

America’s Boldfaced Serial Killers

We see them. We know they’re there. We can’t avoid them.

by daveynin is licensed under CC BY 2.0

A new breed of serial killer has emerged in America. They are the people who, through their actions and inactions, spread the Covid-19 virus.

They don’t wash their hands or sanitize objects they touch. They don’t wear suitable masks, appropriately, all the time. They don’t isolate themselves or get tested. They ignore any symptoms they might have. They congregate closely with others.

They can’t seem to help themselves. They just want life to be good … for themselves. They don’t believe they are doing anything wrong. They don’t see the consequences of their actions. They don’t believe society has the right to restrict their actions. But their pursuit of happiness comes at the expense of others. They expect those others to deal with the harm they inflict.

They are everywhere — at church, at family events, at political rallies, in public spaces. They shop, eat out, throw parties, bar hop, travel, and vacation. They live life as they always have and make no concessions to the pleas of others.

They target the weak, the aged, the ill, and the unprepared. They don’t seem to know or care that they are dangerous. They don’t even recognize if they leave a target unharmed or inflict their curse. They may even turn their target into an unknowing serial killer.

Some of them might get caught, either in the act or later traced by their movements. A test may even confirm their culpability. But they won’t be punished. They’ll be released with only a warning. They will get away with what they have done and go on to resume their spree.

They may not just kill others, they may die themselves. Most believe they will be unaffected, that they will evade the invisible agents they don’t even believe exist. They think they are stronger, and luckier, and more special than the infectious curse they bring on others. But, not all of them will escape those consequences. Then, as a victim, they will feel regret.
Architecture & Style
By: Stanislas Chaillou
Tags: Architecture, Machine Learning, Data Science, Artificial Intelligence

We build here upon a previous piece, where our emphasis revolved around the strict organization of floorplans and their generation, using Artificial intelligence, and more specifically Generative Adversarial Neural Networks (GANs). As we refine our ability to generate floorplans, we raise the question of the bias intrinsic to our models and offer here to extend our study beyond the simple imperative of organization. We investigate architectural style learning, by training and tuning an array of models on specific styles: Baroque, Row House, Victorian Suburban House, & Manhattan Unit. Beyond the simple gimmick of each style, our study reveals the deeper meaning of stylistic: more than its mere cultural significance, style carries a fundamental set of functional rules that defines a clear mechanic of space and controls the internal organization of the plan. In this new article,we will try to evidence the profound impact of architectural style on the composition of floorplans.

Reminder: AI & Generative Adversarial Neural Networks

While studying AI and its potential integration to the architectural practice, we have built an entire generation methodology, using Generative Adversarial Neural Networks (GANs). This subfield of AI has proven to yield tremendous results when applied to two-dimensional generation of information. As any machine-learning model, GANs learn statistically significant phenomena among data presented to them. Their structure, however, represents a breakthrough: made of two key models, the Generator and the Discriminator, GANs leverage a feedback loop between both models to refine their ability to generate relevant images. The Discriminator is trained to recognize images from a set of data. Properly trained, this model is able to distinguish between a real example, taken out of the dataset, from a “fake” image, foreign to the dataset. The Generator, however, is trained to create images resembling images from the same dataset. As the Generator creates images, the Discriminator provides it with some feedback about the quality of its output. In response, the Generator adapts to produce even more realistic images. Through this feedback loop, a GAN progressively builds up its ability to create relevant synthetic images, factoring in phenomena found among observed data.

Generative Adversarial Neural Network’s Architecture | Image Source

We specifically apply this technology to floorplan design, using image representations of plans as data format for both our GAN-models’ inputs and outputs. The framework being employed all across our work is Pix2Pix, a standard GAN model, geared towards image-to-image translation.
Listening at the keyhole
By: Dan Mccarthy
Tags: Writing, Remembering, Human Interest, Seán Ó Faoláin, Religion

Every writer is a man with one deaf ear and one blind eye, who is possessed by a demon and unteachable by anybody but himself; a man who only half hears and half sees the world around him because for half his time he is absorbedly listening at the keyhole to his own Demon, examining with satisfaction his primordial shadow.

If once the boy within us ceases to speak to the man who enfolds him, the shape of life is broken and there is, literally, no more to be said. I think that if my life has had any shape it is this. I have gone on listening and remembering. It is your shape, O my youth, O my country. O pallid clouds. O caverns of green. O rumbling river. O whispering shell.

Sean O’Faolain
Manually computing the coefficients for an OLS regression using Python
By: Roman Shemet
Tags: Python, Regression, Numpy, Ols, Data Science

Python Implementation

Now, to the point of the article. To remain consistent with the commonly used packages, we will write two methods: .fit() and .predict(). Our data manipulation will be carried out using the numpy package. If you’re importing your data from another file, e.g. in a .csv format, you may use the pandas library to do so.

Let us import the modules:

*The matplotlib import will come in handy later if you decide to visualise the prediction

Next, we will create a class for our Model and create a method that fits an OLS regression to the given x and y variables — those must be passed in as numpy arrays. The coefficients are obtained according to the vector form derivation performed earlier (np.linalg.inv() is a numpy function for matrix inversion and @ notation represents vector multiplication):

Our .fit() method stores the computed coefficients in the self.betas attribute to allow them to be accessed later by other methods. Note that we have added an optional parameter intercept; if we decide to fit our model with an intercept, the method will add a vector of 1’s to the array of the independent variables.

We now create the .predict() method:

*Note the extra indentation due to the fact that this method is part of the Model class

Our (very) simple method makes use of vector multiplication to obtain the “predicted” values — y_hat.

As an additional (and optional) touch, we can add a method to visually output the prediction (Note: in the current form, it will only work for a univariate regression with an intercept):

Finally, let us execute the methods we created using sample data (if you don’t want to generate a graph, delete the call to plot_predictions() in line 7 and instead, add the return self.y_hat line at the end of our .predict() method):

If you followed everything along — you should have successfully computed the coefficients and have generated something similar to this:

If you’d like to play around with the code, the full version is available as a GitHub repository here.

Needless to say, this is a very basic exercise, which, nonetheless, efficiently illustrates where the OLS betas come from and what their (mathematical) significance is. Figuring this out has been immensely helpful in my further studies. Lastly, the statistical packages I have referred to earlier, in addition to the computed coefficients, typically calculate a variety of other measures — statistical significance, confidence intervals, R squared and so on. These can all be calculated numerically, however I would advise to rely on the (well-tested) libraries once you’ve understood the underlying concepts.
Pacing
Tags: Family, Father And Daughter, Mental Health, PTSD, Mental Illness

Photo by Sander Weeteling on Unsplash

The sound of pacing bare feet on hardwood floors wakes me up out of a sound sleep. I check my phone- Its 2:13 am. The air is thick with pain.

Slowly I extricate myself from the blankets that envelope my body.

I blindly grope around the dark bedroom for my slippers and a sweatshirt. It's cold downstairs.

I follow the sound of bare footfalls into the kitchen. My father is pacing. Pacing in tight circles around our small table. Pacing. Pacing.

"Hey dad" I call softly. He doesn't respond or acknowledges me. His eyes are open, but his mind is back in the 1980s. He is reliving the worst parts of his nightmares over and over again. I wonder which ghost has come to visit tonight. My eyes brim with tears. Two tears escape; creating twin rivers of saltwater on my cheeks. It never gets easier for him or me.

I take a seat at the breakfast bar and wait. Letting him face this alone is not something I can let him do. When he finally looks at me as if he's looking for me- I'll be here- waiting.

The blue glow of the microwave clock throws a cool light across the kitchen. It's 3:31 am. His gait is starting to slow. This is a good sign.

4:15 am. My dad stops pacing. He slowly turns towards me, his eyes glistening with suppressed tears and a dazed expression. His exhaustion is tangible.

Recognizing that this is the light at the end of the proverbial tunnel, I quickly stand up and make my way towards him. My outstretched arm pulls him into a tight embrace. I can hear his ragged, emotional breaths in my ear. After a moment, I release him from my grasp. We walk to the living room and take our spots on the couch- him to go to sleep- me to keep myself awake until it's time to get ready for work.

Not a word is spoken. It's not needed.
Weekly update #10
By: Live Stars
Tags: Blockchain, Cryptocurrency, Ethereum, Development, Bitcoin

Another week has passed and it is time to share the results with our community.

For the few last weeks we have been mostly focused on creation of Live Stars platform. We have stress-tested the MediaSoup server implementation. It works perfectly on Chrome-based browsers, and now we are making sure that Mozilla Firefox client is also supporting our new server.

Meanwhile, we have also started working on our referral system. Visual bugs and glitches on the website are almost completely gone now. We expect to be able to make our beta test public again after we make sure that the broadcast is working on all of the browsers.

We have seen several complaints concerning the fact administartion has been not that active on social channels lately. This is due to the fact the whole team is now busy with the platform, as it is our main goal at the moment.
Screwed!
By: Pawan Kumar
Tags: Poetry, Relationships, Love, Storytelling, Heartbreak

A happy thought and a sad one.

For him, she’s both.

He knows he’s screwed.
Introduction to Keras & Transfer Learning for Self Driving Cars
By: Prateek Sawhney
Tags: Machine Learning, Self Driving Cars, Artificial Intelligence, Deep Learning, Data Science

GoogleNet

In 2014, Google published its own network in the ImageNet competition and in homage to Yann LeCun and LeNet, Google named their network, GoogLeNet. It’s spelled like GoogleNet but it’s pronounced GoogLeNet. In the ImageNet competition, GoogLeNet performed even a little better than VGG: 6.7% compared to 7.3% percent, although at that level, it kind of feels like we’re splitting hairs. GoogLeNet’s great advantage is that it runs really fast. The team that developed GoogLeNet developed a clever concept called an Inception module, which trains really well and is efficiently deployable.

Do you remember inception?

It’s called an inception module. It’s going to look a little more complicated. The idea is that at each layer of your ConvNet, we can make a choice, have a pooling operation, have a convolution and then we need to decide, is it the one by one convolution or a three by three or five by five. All of these are actually beneficial to the modeling power of our network. So why choose? Let’s use them all. Here’s what an inception module looks like.

The Naive Inception Module. (Source: Inception v1)

Instead of having a single convolution, we have a composition of average pooling followed by one by one, then a one by one convolution, then a one by one followed by a three by three, then a one by one followed by a five by five and at the top we simply concatenate the output of each of them. It looks complicated but what’s interesting is that we can choose these parameters in such a way that the total number of parameters in our model is very small, yet the model performs better than if we had a simple convolution. The inception modules create a situation in which the total number of parameters is very small. This is why GoogLeNet runs almost as fast as AlexNet. And of course GoogLeNet has great accuracy. Like I mentioned earlier, it’s ImageNet error was only 7%. GoogLeNet is a great choice to investigate if we need to run our network in real time, like maybe in a self-driving car.
Your Customized Medium Sub-Domain Profile Has One Less Feature Now
By: Suraj Ghimire
Tags: Social Media, Change, Writing

Your Customized Medium Sub-Domain Profile Has One Less Feature Now

I wish we can revert to the old design

Photo by Helena Hertz on Unsplash

Medium released a new profile layout on the 14th of October. That evening a sub-domain for writers was one of its change-highlight. Earlier, the sub-domain was available only to Medium owned publications but now it is available to all users. On that very evening, we have lost an important feature on Medium.

One of the best features available earlier was to find an article published by a user on a definite publication.

You don’t understand? Let me explain.

My Friend Ryan Fan publishes many articles in a week. So, I may not view all of his stories. However, I don’t want to miss a post he publishes on Koinonia Publication. To find his Koinonia article, I neither need to go through his profile nor I need to google search and type “Ryan Fan Koinonia” (Google may provide, but it is complicated you know!)

Screenshot by author

So what did I do? I mostly applied a simple URL trick. I added a publication URL before his user id and hit enter which showed me the entire post published on Koinonia.

My earlier URL:- medium.com/koinonia/@ryanfan. But now since he customized a sub-domain for him, I will have a tough time finding him.

To the worst, Medium removed this URL trick from everyone's profile. It was a helpful trick. I badly miss it now.

I wish Medium can add this feature one more time.

Talking about the good side, I like the new design. I like how an individual can make their own profile. I like the way how you hide the top writer tag (especially for someone like me who obtained none in the last year)

Yeah, I love this new design of Out of nothing something.

Medium page if you lost out.

Medium Staff, are you listening? If you can hear me, I would suggest one more important feature to be added. I would want a personalized notification for my favorite writers. I know irrespective of distribution or not; you mail me your best post from the people I follow on Medium. But I want something more.

I do not want to miss stories of some specific writer, and I want to click a notification bell on their profile so every time they post something, even if I am the only person to read that article, I want a real-time notification/mail so I can read them without depending on your algorithm.

While I still wish if we can revert to the old URL trick, I hope Medium can manage some changes so I can search for my favorite writer as per the publication. Also, please add a notification bell on every profile.

I have a few more suggestions but will write later.
Google CoLab Tutorial — How to setup a Pytorch Environment on CoLab
Tags: Deep Learning, Colab, Jupyter Notebook

3. How to Install Python Library in Colab

Colab has command line support, so simply add ! exclamation mark to run Linux commands in the cell. You can simply run !pip install <package-name> to perform pip install. So when you go to Pytorch official installation website, and choose the specifications of the pytorch version you want to download, make sure you choose Linux, Pip, and Python, and then the CUDA version you want to install, and you would see a pip command line shown at the bottom:

Then copy paste that command to CoLab cell with a prefix !

So, simply run !pip install torch trochvision in the CoLab cell:

Then after it runs, the package is successfully installed.

Note: It seems that CoLab has already preinstalled Pytorch for you, so if you run this command, it’ll tell you “Requirement already satisfied”. However, you can use the same method to install any other python package through pip install.
7 Figma plugins that you need in your life
By: Marc Andrew
Tags: Web Development, UI, Figma, Design, UX Design

Originally published at marcandrew.me on September 24th, 2020.

There’s no denying that Figma is already a powerful, and versatile design tool out-of-the-box.

It continues to improve with each new release and has rightly claimed its place in the ‘Big 3 Design Tools Club’ (the others being Sketch & Adobe XD of course).

But, up until around a year ago, Figma was at a disadvantage against a tool such as Sketch.

Why?

Plugins.

Of course that’s no longer the case and the Plugin community for Figma is thriving, with more, and more powerful, and invaluable plugins being added daily.

In this article I wanted to share a few of the plugins that I use on a regular basis, and that have helped me not only improve the designs I create, but have also helped speed up my workflow considerably. And I’m sure they’ll do the same for you.

Let’s get to it…
Sometimes your audience on social media surprises you.
By: Thomas Smith
Tags: Marketing, Short Form, Social Media, Moderation, YouTube

Sometimes your audience on social media surprises you.

I was recently scrolling through my comments on my gadget-centered YouTube channel, and saw a negative comment about one of my videos. I usually delete comments that are negative and hostile, and keep comments that are merely negative and critical.

This one fell into the former category, so I was about to delete it, when I saw that a random follower of my channel had seen the comment and leapt to my defense.

It’s a reminder that for every nasty troll on the Internet, there’s a troll-buster ready to fight back. I don’t know who you are Aquaboy, but I’m thankful for you.

Read more about the benefits of negative comments and my strategies for managing YouTube comments in my article in Better Marketing.
My Favorite Books About Books (so far)
By: Abigail Siegel
Tags: Adventure, Books, Books About Books, Reading, Stories

Weird Things Customers Say in Bookshops by Jen Campbell

This is a book that talks about all the weird and wonderful experiences booksellers have had with their customers. It will make you laugh to no end, and perhaps you will find some cool reads along the way! Or maybe even find out what not to read!

The Encyclopedia of Early Earth by Isabel Greenberg

This graphic novel isn’t really about books, but it is about stories and the way stories shape us. A young man from the farthest reaches of the world travels far and wide from one adventure to another, telling stories of myth and folklore to those he meets. Each tale shows a bit of how each person and culture relates to the stories, and how the young man impacts those who he has met.

Tilly and the Book Wanderers by Anna James

This is a book about people who love to get lost in books. Literally. Tilly lives with her grandparents, who run the bookshop Pages & Co. Her whole life she has been surrounded by books. Then one day, she discovers that she and many others have the ability to travel within books. Tilly starts by traveling into her favorite stories like Anne of Green Gables, but soon finds that bookwandering can be tricky, and gets into some adventuresome trouble! Wouldn’t we all just love to have a short adventure inside a book?

Fahrenheit 451 by Ray Bradbury

This is a book about the importance of books. In a dystopian world where books are banned, and anyone caught with them is either arrested or killed, we remember the importance of the written word. Our main character, a fireman (someone who burns books for a living), realizes there is nothing in the ignorance they’ve all been brainwashed to love. He starts to read the books he’s meant to burn, and his attitude towards books, to life even, changes.

The Little Paris Bookshop by Nina George

If you need a remedy for a malady of the soul, this book is for you. A man works on a book barge, prescribing specific books for specific maladies of the customers that come to peruse. When the man, depressed at the loss of his love, realizes that his love has not been lost, merely misunderstood, goes on an adventure to discover the truth. On the way he meets new friends, and new books!

The Shadow of the Wind by Carlos Ruiz Zafon

Everyone likes a good mystery, but a mystery about a book? Even better. In this book we read about the life of a young man in Spain who’s sole mission is to find out everything he can about a book he found in the “Cemetery of Forgotten Books”. The young man finds love and friendship on the way, but most importantly, he finds the truth.

These are my favorite books about books so far. I will update the list once I read more!
Multisignature Wallet for ETH and ERC20 Tokens
By: Dapp Builder Team
Tags: Token, Ethereum, Development, ICO, Blockchain

We have created an extended version of Multisignature Wallet dApp. This wallet is applicable not only for Ether, but also for ERC20 tokens. Try it now in our Marketplace.

New Multisignature Wallet creating

If you need to use Ether and ERC20 tokens in your wallet — this solution is for you. If you need a wallet only for Ether, it’s better for you to create an older version of the Multisignature Wallet dApp, because it needs less Gas for creation.

New Multisignature Wallet interface

For using your ERC20 tokens in your multisignature wallet you need to send them directly to the Wallet address and then add them in the Wallet interface by entering the token’s smart contract address.

Adding tokens and tokens list

The mechanism of sending multisignature transactions with tokens is the same with sending Ether. One of the wallet’s owners creates a transaction, and then it must be approved by neccessary number of owners, then transaction is able to be sent.

Token sending transaction

Try it now on https://dappbuilder.io/builder

Or watch the code on https://github.com/DAPPBUILDER/dApp-Builder

Stay in touch for for updates via
5 More macOS Apps For Your Work Life
By: Abhinav Chandoli
Tags: Technology, Apple, Mac, Debugger, Software

5 More macOS Apps For Your Work Life

Apps for a Better Work Life

Photo by Josue Valencia on Unsplash

Apple’s macOS has always been one of the go-to Operating systems for many professionals in various industries. The main or simple reason can be is It just works. Apple always brags about it for its less complex, fast, and smooth user interface.

Even though there are some obvious advantages in using macOS, there are equally obvious downsides in using it, especially for professional use cases. However, we can at least try to make them seem less obvious downsides by tinkering with the OS. Try out these few apps to make your work life a bit easier.
Why Nike’s move to play the fence works to their benefit
By: Shamontiel L. Vaughn
Tags: Marketing, Adiversity, Kaepernick, Controversy, Nike

When entertainment, politics and business collide

When companies attach themselves to a public figure, they cross their fingers and hope that their brands don’t somehow get ruined if the celeb decides to go off the rails. With that said, some consumers are pretty good at separating “the art” from the politics. Others simply refuse to separate the two. Then there’s a third group that falls more into a gray area.

For example, actor/director Kelsey Grammer is open about being a Trump supporter. But there’s no denying his quiet production credit for the eight-year, legendary African-American sitcom “Girlfriends.”

Kanye West considers the current president a “father figure,” but even former fans who are against his politics still gave the rapper’s ninth album “Jesus Is King” a shot. It soared to the top of the Billboard charts, with 197 million streams and 109,000 copies sold as a full album during its opening week — much to the relief of Def Jam Recordings and Universal Music Group.

Comedic actor Ashton Kutcher endorsed former, two-time presidential candidate Hillary Clinton but still starred in the Netflix series “The Ranch.” And Sam Elliott, who also stars in “The Ranch” as a conservative-leaning father, hasn’t hidden his anti-Trump views either. Meanwhile, Netflix is also giving viewers the option to skip Trump jokes altogether in comedian Seth Meyers’ latest comedy special.

On the opposite side, ABC stopped ignoring Roseanne Barr’s Twitter rants on politics and race, and removed her from the reboot of her own ’80s sitcom. Season two of the show became “The Conners,” which still kept its conservative-leaning theme but made Dan Conner a widower. Meanwhile, John Goodman and the rest of the cast saved the show — even after John Goodman suggested Trump supporters build their own dome away from everybody else.
5 Persuasion Techniques That Aren’t Manipulative
By: Barry Davret
Tags: Relationships, Leadership, Psychology, Self Improvement, Life Lessons

On an otherwise routine Monday in 1994, I witnessed a remarkable demonstration of persuasion.

I was a stockbroker trainee on Wall Street at the time. On a typical Monday, my boss’s nail technician would come to the office for his weekly manicure/pedicure. I sat at a desk across from his, and thankfully I faced a wall.

But on this day, with his nail tech doing her thing, he commanded me to turn and look at him. He wanted to train me.

“I can persuade anyone,” he said in his thick Brooklyn accent. “Listen.”

With the speakerphone blaring, he finessed his way past the receptionist and assistant, and finally landed the prospect. And then he patiently endured a tirade of foul-mouthed language. “Now, I’ll turn him,” he said after muting the phone.

And he did. He then repeated his success on two more people, generating sales that totaled tens of thousands of dollars.

With his nail technician now working on his feet, he said, “That paid my rent.”

Years later, I found a mentor who followed the same principles but without the theatrics. In fact, he was a quiet person like me. He proved that you don’t need flashy charisma or charm to master the art of persuasion. You only need to learn and practice the principles.

And if you’re worried about being manipulative, that’s a good thing. Keep your intent honorable and be honest. Above all, remember that it’s your job to help the other person change their mind, not to decide for them.

These five techniques may surprise you. Some contradict conventional wisdom, but the best persuaders follow them diligently.
Submission Guidelines
By: Flannery Wilson
Tags: Literature, Philosophy, Publication, Storytelling, University

Submission types

Articles and short essays: research (always with Works Cited), and opinion.

Short stories: should be relevant to the journal theme, which changes issue by issue.

Aim and Scope

This journal began as a response to our fundamental concern with current materials available to students — and to others looking for new approaches.

We worry that students are alienated by pretentious academic jargon that does not appear relevant to everyday experience. (Please see “Adapting the Humanities in 2020”).

We are also interested in general opinion pieces, about the present state/future of the humanities.

Please note

· All essays must be no longer than 1500 words (a 6 minute read).

· Must be written clearly with the aim and scope of the journal in mind.

. Criticism and theory should not be unnecessarily jargon-laden.

· This journal is intended for a broad readership. We encourage all of our authors to promote and share their articles on social media.

· If you are enrolled in Medium’s partner program, your essay is eligible to earn money.

· Don’t assume that your readers know the definitions of technical terms.

· Be sure to read the newest call for papers carefully. These will also be posted on the Penn CFP site.

· Please send proposals first before sending full articles.

Thank you

Please send all initial proposals to: humanitiesintransition@protonmail.com.

We will only contact you if we think your proposal looks promising.

We look forward to reading your submission!
The Obscure Legacy of Stephen Dixon
By: Nathan Gelgud
Tags: Stephen Dixon, Olivier Assayas, Books, Comics, Autofiction

Comics, often about movies || New York Times, The New Yorker, Hyperallergic || A House in the Jungle, Koyama Press || @gelgud || www.nathangelgud.com

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Taiwan Data Science Meetup｜集合啦！程式語言麻瓜會！文組也能做資料工作？
By: Wendy Hsu
Tags: Data Analyst, Careers, Meetup, Business Intelligence

從 Marketing 到 Data，我在 17 的轉職之路

From Marketing to Data, My Career Roadmap in 17Media.
Motor Planning
By: Victoria Ponte
Tags: This Happened To Me, Mental Health, Disability, Stroke, Gratitude

Unsplash

Motor Planning

What it’s like when half your body doesn’t work properly

From Study.com:

Motor planning is the ability to assess a motor activity, plan and organize how to carry out that motor activity, and finally implement motor skills to achieve that motor activity.

I became aware of the term motor planning at a recent physical therapy session where the therapist asked me to complete a simple task of walking up a step then placing an object on the adjacent window sill. I told her how I planned to do each step out loud. She commented this was good motor planning. It was then I realized what a big part of life this is.

Most of us don’t think about motor planning. We take it for granted because it’s automatic. I have been gifted with a disability which makes me appreciate every move I make.

The left half of my body became paralyzed when I had a stroke at 35. I slowly had to re-learn how to move. My body has never fully cooperated in the 20 years since the stroke.

This forces me to engineer every movement and activity of daily living. From getting clothes on and off, to getting groceries into the house from the car, I have to mentally map out each move considering the limitations of my body.

My fine motor skills in my left hand are nearly nonexistent. My arm and leg are weak. My foot is paralyzed. My balance is poor. I carry a cane in my functioning right hand so I can’t always use it when I need it.

I spend every waking minute planning how to get by without the help of my left hand. This often means I rest my cane somewhere so I can carry something with my right hand. I walk ok without the cane for short distances. When I finish what I needed my right hand for, I regularly forget where I left my cane.

Ingenuity is my friend. I don’t usually realize how glaring it is when people watch me that I effectively ignore my left hand.

For instance, a teller at the drive through lane at the bank once asked what was wrong with my left hand since I reach across to the transaction drawer with my right. He was shocked and embarrassed when I told him I’d had a stroke.

It is exhausting to have to put so much thought and effort into getting through the day. Things that were once simple and automatic have become inordinately complicated.

Having physical limitations doesn’t seem as bad to me as having cognitive deficits would. I am grateful for the ability to assess a motor activity, plan and organize how to carry out that motor activity and figure out a way to implement it even if it isn’t elegant.

Having a minor disability has given me an appreciation for what totally disabled people have to deal with; and I take much less for granted.

I hope my story gives you a sense of gratitude for the automatic ease with which your body functions.
The Dawn
Tags: Poetry, Poems On Medium, Dawn, Nature, Writing

Driving down that road,

The lanes where farms ran across

Stars and moon looking from the sky

Gently caressing the sleepy crops

The cool soothing breeze rolls

Gently washing my face

Conveying the goodbye of the moon

To wake up my eyes and soul

The curls in my locks stretch

And all aquiver danced on my forehead

The breath deeply feels the zephyr

With the rising Sun, far, on the horizon

Sky’s silver touch turns slightly rouge

Moon being painted and some stars fading through

As the sun rises from its home

So mellifluously accepts the reins from the night’s crew

The shinning moon, now, quietly conceals

A few zealous stars hold on to bask in the Sun’s hues

And when the sunlight sprinkles its golden aura across

They too, follow the moon’s lead, internalizing their pause

The lingering softness of the cool breeze

Even to the warmer sun-rays, seem to enchant

The lingering darkness gradually trickles into oblivion

When the dawn gives way to the morning song

The Sun lifts up the sky, in full vigour

Waking up the last of the sleepy wings

Lending the colours to the grass beside

Warming the souls and the air alike!

© GK
New Features in Python 3.9
By: James Briggs
Tags: Python, Technology, Code, Data Science, Programming

Dictionary Unions

One of my favorite new features with a sleek syntax. If we have two dictionaries a and b that we need to merge, we now use the union operators.

We have the merge operator | :

a = {1: 'a', 2: 'b', 3: 'c'}

b = {4: 'd', 5: 'e'} c = a | b

print(c)

[Out]: {1: 'a', 2: 'b', 3: 'c', 4: 'd', 5: 'e'}

And the update operator |= , which updates the original dictionary:

a = {1: 'a', 2: 'b', 3: 'c'}

b = {4: 'd', 5: 'e'} a |= b

print(a)

[Out]: {1: 'a', 2: 'b', 3: 'c', 4: 'd', 5: 'e'}

If our dictionaries share a common key, the key-value pair in the second dictionary will be used:

a = {1: 'a', 2: 'b', 3: 'c', 6: 'in both'}

b = {4: 'd', 5: 'e', 6: 'but different'} print(a | b)

[Out]: {1: 'a', 2: 'b', 3: 'c', 6: 'but different', 4: 'd', 5: 'e'}

Dictionary Update with Iterables

Another cool behavior of the |= operator is the ability to update the dictionary with new key-value pairs using an iterable object — like a list or generator:

a = {'a': 'one', 'b': 'two'}

b = ((i, i**2) for i in range(3)) a |= b

print(a)

[Out]: {'a': 'one', 'b': 'two', 0: 0, 1: 1, 2: 4}
3 common mistakes when doing content experiments
By: Arjan Haring
Tags: Marketing, Ecommerce, Experimenting

#2: Test concepts that are too complex (or unclear)

In the early days when I was training people at Booking.com I used different sets of “innovation cards” (Mental Notes, Design with Intent Toolkit & Brains, Behavior & Design) to inspire new content ideas.

On each of these cards there is a summary of a psychological principle and how you could apply that to content. The very first trainings I did I used all 3 sets to inspire new ideas. I had an enormous pool of concepts and principles that people could choose from. I thought that was a good thing.

Although it wasn’t difficult to apply the different concepts and principles, translating it in a clear experiment was less easy. Let’s take the examples of the Endownment effect and commitment mentioned earlier. These are some of the more complex concepts you can use to create content experiments.

Actually a lot of scientific work is more complex to translate into content.

Let’s take also return that as an example and let’s go back to the shopping cart example. And just for fun let’s use the lean startup hypothesis template for the endownment effect:

We believe [a person who visits our website] has a problem [shopping]. We can help them with [giving him a sense of ownership before he really owns the specific product - adding a product to a shopping cart increases the sense of ownership]. We'll know we're right if [those website visitors will be less likely to abandon the things in the shopping cart]

And for commitment:

We believe [a person who visits our website] has a problem [shopping]. We can help them with [making shopping easier by cutting it in some smaller steps- adding a product to a shopping cart will ask a lower level commitment]. We'll know we're right if [those website visitors will be more likely to buy in a next step]

We can see that the shopping cart feature could be used in both hypotheses. And the hypotheses are very similar. Teasing out causality there is rather difficult. It’s a cool challenge, but maybe not something you want to start with.

Luckily for us, there are also pretty straightforward concepts. For example Social Proof: If other people do it, you are also more likely to do it. Translating that into content is rather easy, and I haven’t seen many mistakes made there. Just because it’s way less ambiguous.

Check out this:

We believe [a person who visits our website] has a problem [shopping]. We can help them with [making shopping easier by showing the most popular product (for his/her profile)]. We'll know we're right if [those website visitors will be more likely to buy in a next step]

If the most popular product also happens to be an staff’s pick, or on discount until the end of the week, it get’s more tricky. But in general I advise companies to start with those concepts that they are very sure of, and that are as little ambiguous as possible.

#3: Test changes that are too subtle
Using Docker as a Data Scientist
By: Aleksandar Gakovic
Tags: Python, Docker, Containerization, Containers, Data Science

Good day everyone!

The ship with our data science project is just arriving off the port! Get ready to unload the containers and fire up the environment. Wait… what? Wish it was that easy to go? Well, it basically is. Welcome to Docker!

In this article, we are going to learn

How to install Docker Desktop

How to docker — Docker images and Docker Hub

How to Docker — Docker Containers

Run a complete data science project with Docker

Docker is a modern breakthrough. A way in which we can save and share our projects complete with their original environments. No more incompatibility shenanigans and it's quick and easy. Anyone can take a docker image from a docker image registry, download it, run it and begin working in the same environment the project was built in. I explain what Docker is and how it works in my article What the hell is Docker?!

The ability to reproduce project results over different machines is incredibly important in data science. Docker makes this incredibly easy.

Photo by Noah Carter on Unsplash

If you’re ready, let's get going
Learn the basics of the Ethereum JSON API in 5 minutes
By: Nicolas Schapeler
Tags: Python, API, Blockchain, Ethereum, Programming

Learn the basics of the Ethereum JSON API in 5 minutes Nicolas Schapeler Follow Apr 5 · 2 min read

Photo by Shahadat Rahman on Unsplash

The other day I got myself in a situation where I needed to communicate with the Ethereum network using python in an environment where getting web3.py to work seemed pretty much impossible. Since I still needed to talk to the network, I resorted to using the JSON-RPC API provided by Ethereum, which all web3 libraries are built on top of. Turns out, it’s pretty interesting! So, let’s get started!

Basic setup

First things first — let’s declare a few variables that will be helpful when sending requests later:

To keep things simple, we use an Infura Node to connect to the Ethereum Ropsten Testnet. You can get an API Key for that here.

Your first request

Let’s get our feet wet by fetching the current gas price of the network. We can do this by simply doing:

How did I know what method to use and what parameters to send? It can all be found in the official Ethereum docs.

Getting the latest Block

Let’s try something a bit more interesting — let’s fetch the latest block and see what we can read from there!

Let’s have a closer look at one of the transactions:

You’re probably starting to get the pattern of how these calls work, so let’s try something a little more advanced:

Sending Transactions

First, let’s create a new account using the web3.py library and load it with some Ropsten ether. I like to use this faucet.

To send a transaction, we need the nonce. This too we can fetch with the RPC JSON API using the same pattern as above:

Next, we create and sign our transaction and send it off using the JSON RPC API once more:

If you’re testing on a different Ethereum (Test)net, make sure to set the chain Id accordingly.

Notice how we were able to reuse the gas price which we fetched at the beginning.

Conclusion

And that’s all! You just learned the basics of interacting with the most influential blockchain in the world using the JSON RPC Ethereum API! You can find the code for all this here.

Thanks for following along!

Nicolas

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