Same here. Really interested.
Guys do you suggest going through the Spring 2017 version of CS231N or the 2016 version?
Andrej Karparthy had taught the 2016 version.
Obviously 2016 version…
I had watched them till 10 lectures
Despite how relatively little math I know, I find that my ability to do deep learning has been and continues to be bounded by ‘simple’ (simple is probably not the right word here), non-mathy things.
For instance, just right now I am using bcolz.ctables for the first time ever, a couple of days ago I learned a bit about Python generators, not too long ago I learned about ssh tunnels and use them to connect jupyter notebook running on my box…
What a reasonable person would do in such a scenario? Focus on the non-mathy things that seem to work! What does Radek do? Is attracted like a moth to a lightbulb to all sort of math related books despite all the evidence pointing to the contrary! Guess what I asked Santa to bring me this Christmas Ah the old wiring is not easy to overcome!
Well, thankfully not all is lost and through the guidance of Jeremy and Rachel and the through the copious amounts of time I sunk into things that didn’t bear fruit in the past, and also thx to not having too much time nowadays or at least as much time as I would like to give to DL, I tend to focus on the stuff that works ever so slightly better
What does Radek do? Is attracted like a moth to a lightbulb to all sort of math related books despite all the evidence pointing to the contrary!
oh man, iso +1 on this. though i can reasonably hack my way around, the inability to appreciate all the math in the relevant DL papers bugs me to no end
I have to agree that the bottleneck in my performance is due to lack of ‘simple’ knowledge
But then there is again the confusion, should I know this much theory for a little boost?
I found the CS231N-CNN Stanford course helpful. The assignments definitely help if the not the lectures (lectures are definitely theory intensive), assignments even though practical-are not very advanced topics. And I always find myself in the midst of the confusion.
Here’s an upcoming book on building a bot that can play Go:
new book to be available by François Chollet
Could you please recommend a python MOOC that could serve as a prerequisite to this course?
Edit: I have just finished engineering degree, thus I have some programming experience. Also I did some basic programming in python already. I’m looking for a course that reviews the language, makes you think and is not terribly boring
I found Andrew Ng’s deeplearning.ai specialization to be excellent preparation for fastai.
For a complete Python noob: Automatetheboringstuff.com
You’ll still need to learn stuff like Numpy, Pandas, and some basic ML after this before you’ll be ready for fast.ai but you should have an excellent grasp of the basics of Python about half way through this book and can start copying and pasting code from Github and Stackoverflow for more advanced stuff at that point.