Building Neural Nets From Scratch in 3 Chapters
- Pytorch Edition
In this session, we will cover how neural nets work and why libraries like Pytorch, Tensorflow and others are so useful in implementing them in practice!
We will start by understanding how a linear regression works and then implement one from scratch in our three chapters: plain Numpy, "raw" Pytorch and again in Pytorch with all the helpers enabled!
Then we'll build a simple neural net in Pytorch, both raw and high-level!
Slides are on Google Slides