Lesson "0": Practical Deep Learning for Coders (fast.ai)
Channel: Jeremy Howard
Date: 2021-05-26

This is an optional video that can be used to help you get through and make the most of Practical Deep Learning for Coders, https://course.fast.ai. I discuss what students of the course have found most useful in getting through the lessons successfully. I also show how to set up a Linux GPU server from scratch on AWS EC2. (Note, this isn't the start of a new course - it's a new video to go with the existing course).

Here's a link to the book by Radek Osmulski which I discuss in the talk: https://gumroad.com/l/learn_deep_learning

00:00 - Two groups of students in general
02:01 - The fastai book
02:55 - The course
03:22 - Finish the course!
04:27 - Finish a project!
05:49 - What can a project be?
06:53 - Be tenacious!
08:27 - Radek Osmulski story
10:15 - Stop endlessly preparing for doing deep learning
11:16 - What will fastai teach you
12:25 - How to get started with coding
14:00 - The missing semester of your CS education
15:30 - Share your work or learning
17:25 - four steps to do fastai lessons
20:32 - Notebook Server vs Linux Server
23:43 - Get started with Colab
29:37 - Github with Colab
30:37 - Clean version of notebook
31:26 - Questionnaires
32:32 - Share your model on your dataset
34:29 - Wrong ways to do fastai
36:41 - Start positive learning feedback
37:27 - Read and Write code
38:07 - Immerse yourself in DL world through twitter
40:39 - Go blogging
42:03 - A great thing to blog
44:03 - How ML differs from other coding
45:15 - Why and How to create a good validation set
46:20 - Coding DL is harder than other forms of coding
47:16 - Baseline for your project
49:51 - Kaggle competitions as best projects
52:33 - Build your portfolio for job
55:30 - Get to be the firsts to do part 2
56:08 - How to get started with AWS EC2

Thanks for "Daniel 深度碎片" from forums.fast.ai for providing the timestamps.