Building core Deep Learning algorithms in Rust.
It's kinda like the middle child of karpathy/micrograd and geohot/tinygrad.
Any type of contribution is welcome as long as it adds value! i.e
- Bug fixes followed with tests to ensure the bug never resurfaces
- Increasing code readability, or run-time/memory efficiency
- Completing a To-Do task
- Weight Initializers
Create optimizer module for optimization algorithms- Convolutional Neural Networks
Convolutional Layer- Pooling Layer
Padding Support- Padding Type
Dilation Support