Reusable Maching Learning Components

A library of Machine Learning models and algorithms written in Python.

This library goes alongside my Machine Learning demonstration graphical application located at https://github.com/jamalmoir/ml_demo

IMPLEMENTED

• Forward Feeding Backpropagation Artificial Neural Network
• Decision Tree trained via the ID3 algorithm, in combination with K-Means clustering to handle continuous data.
• K-Means Clustering

TODO

• K-Nearest-Neighbours
• Logistic Regression
• Linear Regression
• ???

ROADMAP

• Develop forward feedining backpropagation Artificial Neural Network
• Change Neural Network to use an adaptive learning rate
• Add support for saving Neural Networks to and loading them from pre-trained models
• Add hyperbolic tangent as a activation function
• Develop Decision Tree trained with the ID3 algorithm
• Add support for saving Decision Trees to and loading them from pre-trained models
• Develop K-Means clustering model
• Add support for continuous data to the Decision Tree
• Develop K-Nearest-Neighbours algorithm
• Develop Logicsitc Regression algorithm
• Develop Linear Regression algorithm