I'd like to learn PyTorch. So I'm going to use this repo to:
- Add what I've learned.
- Teach others in a beginner-friendly way.
Stay tuned to here for updates. Course materials will be actively worked on for the next ~3-4 months.
Launch early 2022.
Note: This is rough and subject to change.
- PyTorch fundamentals - ML is all about representing data as numbers (tensors) and manipulating those tensors so this module will cover PyTorch tensors.
- PyTorch workflow - You'll use different techniques for different problem types but the workflow remains much the same:
data -> build model -> fit model to data (training) -> evaluate model and make predictions (inference) -> save & load model
* Module 1 will showcase an end-to-end PyTorch workflow that can be leveraged for other problems.
- PyTorch classification - Let's take the workflow we learned in module 1 and apply it to a common machine learning problem type: classification (deciding whether something is one thing or another).
- PyTorch computer vision - We'll get even more specific now and see how PyTorch can be used for computer vision problems though still using the same workflow from 1 & 2.
- Going modular - PyTorch is designed to be modular, let's turn what we've created into a series of Python scripts (this is how you'll often find PyTorch code in the wild). For example:
code/
model.py
training.py
eval.py
- ???
Still tossing up ideas for the last one. Possibly a two scaled up projects to emphasize everything in 2, 3, 4.
Some ideas: transfer learning + replicate a modern paper with pure PyTorch?
Almost daily updates of what's happening.
19 Oct 2021 - Start repo 🔥