Machine learning algorithms implementation

This repository consisits of implementation of various machine learning algorithms. The algorithms implemented have their own folders, and description of the algorithm and other detail are attached to the folder itself.

Currently, the algorithms implemented are as follows:

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

All the algorithms support datasets in which features are divided into columns (features) and the classification is in the last column. The algorithms also support any number of lines in the training data.

All the algorithms are written in python. The description of algorithms are also found inside the each algorithm folder.


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