Simple machine learning algorithms implementation

This repository consists implementation of various machine learning algorithms.

Steps to run

1. Clone, fork, or download the repository
2. Navigate to the respective algorithm folder
3. Insert the datasets matching the description provided in the algorithm
4. Run the respective algorithm using Python

Description

Currently, the following algorithms are implemented :

1. Naive Bayes Calssifiers
2. Linear Regression
3. Neural Networks and Backpropagation
4. Decision Trees
5. K-Nearest Neighbour Clustering
6. Value Iteration

Future Implementation

• Front end system and support for more datasets are planned

Dependencies

• Numpy