What's up guys, Just wanted to share the humble beginnings of a Deep Learning framework I'm developing based on Sentdex's NNFS (Neural Networks From Scratch) [book](https://nnfs.io) / [YouTube series](https://youtu.be/Wo5dMEP_BbI)
I call it [NimNet](https://github.com/Niminem/NimNet) The framework will be written in pure Nim- standard lib only, no dependencies. I had originally worked through parts 1-8 of the series using the `neo` library without issues, but I really wanted to understand the math involved behind everything... and a pure Nim Deep Learning framework just sounds really f*****g cool. That being said, the math module I wrote is absolutely atrocious right now- completely unoptimized and lacks any exception handling. But it works for what's written so far! As I become a better Nim developer I'll be reworking the math and other implementations. `main.nim` currently combines all of the functions & math I've written if you'd like to see what that looks like.
