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