mlscratch 0.1.0

Machine learning from scratch

Machine Learning From Scratch

About

Practical implementations of common machine learning algorithms with test cases coded from scratch in a similar style as Scikit-learn using Object-Oriented Programming.

This project is meant to increase our understanding of machine learning algorithms and what is 'underneath the hood'. It is not meant for use in actual data science work.

Installation

To use the classes and functions for testing purposes create a virtual environment and pip install the project.

    $ pip install mlscratch==0.0.1

To download all source code in a local repository from Github create a virtual environment and run the following commands in your terminal.

    $ git clone https://github.com/lukenew2/mlscratch
    $ cd mlscratch
    $ python setup.py install

Learning Algorithms

Supervised

• Elastic Net
• Lasso Regression
• Linear Regression
• Logistic Regression
• Polynomial Regression
• Ridge Regression
• Softmax Regression

Write-Ups

• ML From Scratch: Linear, Polynomial, and Regularized Regression Models