fast.ai v3 lessons 5-min summaries
I’m doing fast.ai’s fantastic course called Practical Deep Learning for Coders.
Version 3 of the course was just released, and although I was close to finishing version 2, I decided to go back and do it again.
The format of the course is such that the lessons are 2-hour lectures, and assumes no prior knowledge (except 1 year of coding experience). As such, much of the lessons can be old hat for someone a bit more experienced (namely the Jupyter stuff, and Python programming), but there are also some great insights to do world-class deep learning in the lessons that you really can’t find elsewhere.
As such, I decided to make some 5-minute summaries of what I thought was noteworthy for my own reference (which may or may not take 5 minutes to read), and for anyone else who’s interested.
It should go without saying that this is not a replacement for the course, and you should definitely watch the videos and run the notebooks.
If you are interested in a more detailed summary of the lectures, the best resource is probably Hiromi Suenaga’s fantastic notes.