A tool for understanding :)
For best results, use Python 3.9.
Please use python -m pip install -r requirements.txt to install the dependencies.
In this repo, I'm implementing classic machine learning algorithms from scratch with NumPy. Here's what we have so far:
- Exploratory Data Analysis - see the
analysispackage. - Linear/Polynomial Regression via OLS - see the
models.supervised.regression.olsandmodels.supervised.regression.linear_via_backpropmodules. - Unsupervised Learning via K-Means Clustering - see the
models.unsupervised.clustering.kmeansmodule. - For supervised models that use backprop: we have
monitor.py, to record the learning curves. - Optimizers: so far has
gradient_descent.
