decepticon captures my learnings about ML through implementing and
experimenting in Rust. This is loosely following a couple of blog posts I've
found on implementing a simple feed forward network from scratch.
- https://victorzhou.com/blog/intro-to-neural-networks/
- https://machinelearningmastery.com/implement-backpropagation-algorithm-scratch-python/
My primary goal is to learn about data science. It's something I wrote off for a while, but now that I'm outside of academia I feel like I can learn it more practically for fun. Some other things of interest:
- Do some math - I haven't written out math on paper in a while, and I'm interested in the math behind machine learning.
- Experiment - see if I can build a thing that seems to "learn".
- Play with Rust - I've written a little bit here and there, but haven't kept up with the language lately, and I'd like to get back into learning Rust best practices and design patterns.