Fundamental Machine Learning Algorithms in Numpy
This is an ongoing repository where I will be implementing all the fundamental algorithms in machine learning from scratch using Numpy. The goal of this repository is to better my understanding of how these algorithms work and get a better intuition.
All of the code is written in Colab Notebooks and can be run through Colab or your local Jupyter notebooks (you will have to edit certain cells that mount G-Drive)
Current Implementations
- K Nearest Neighbors
- Linear Regression
- (Experiment) CIFAR-10 on PyTorch... Just for fun
NOTE: Feel free to add any issues or questions :)