abrosua / ml-with-numpy

Machine Learning models implementation using NumPy and NumPy only

Machine Learning with NumPy

These are the simple NumPy implementations for some of the most popular Machine Learning (ML) algorithms, such as:

1. Linear Regression
2. Principal Components Analysis (PCA)
3. k-Nearest Neighbors Regression

Getting Started

File Structure

• benchmark--- benchmark scripts
  • Installing other packages is needed to run the benchmark models (e.g., sklearn's PCA, OLS Regression, and k-NN Regression; statsmodels' Quantile Regression)
• demo --- demo scripts
• models --- scripts for each model

Built With

Python 3.6.9, with the following packages:

• NumPy 1.17.4
• matplotlib 3.3.0*
• scikit-learn 0.21.3*
• pandas 0.25.0*
• statsmodels 0.12.2*

*Note: These packages are NOT required to run the models! Only install it to run the benchmark scripts.

To install the packages, please run the following command,

pip install -r requirements.txt

License

This project is licensed under the MIT License - see the LICENSE file for details