Hi everyone! While waiting for my copy of Deep Learning for Coders with fastai and PyTorch to arrive, I have decided to start reading Deep Learning with Pytorch (2nd Edition) by Eli Stevens, Luca Antiga and Thomas Viehmann.
Inspired by this awesome community and my virtual friend @muellerzr, @init_27 I decided to record myself and share it with you all. My idea is to keep reading and adding new videos every day since as I am now in self-isolation for 10-days due to covid-19 it also helps me feel a bit less alone.
@mgloria awesome idea! I got through the first part of Deep Learning with PyTorch and then when I hit the project for part 2… the data processing stage really threw me off (lol). Luckily the FastAi book arrived the next day.
Nonetheless, I really did appreciate part 1. Maybe I’m a bit dense – but some concepts like the tensor data structure (and modules etc) finally started to make sense once I was forced to sit down with the book. It also has helped immensely with my understanding of FastAi. Will be interested in seeing how you take on part 2!!
There’s a cool Kaggle competition right now with a similar CT scan dateset that I decided to try working on in order to get a better intuition of working with dicoms. Should also circle back around and work on part 2 with the FastAi DataBlocks.
About halfway through FastAi book and I must say… both books have been exceptional companions during this pandemic these past few weeks
Hi @ali_baba thanks a lot for the support!! So far part 1 seems very interesting, let’s see if I can manage to get to Part 2 very fast. I will check the dataset you mention, can be an interesting problem to work on parallel.
I just created a playlist to keep adding videos in a more organized way
Looking forward to your videos on this topic!
So far part 1 seems very interesting, let’s see if I can manage to get to Part 2 very fast. I will check the dataset you mention, can be an interesting problem to work on parallel.
