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MachineLearningAlgorithms

This repo tries to implement some of the traditional machine learning algorithms with helps from other machine learning experts and their repos.
The algorithms are tested with the MNIST dataset, to download: MNIST handwritten digital database
Performance is not optimized, made only for self learning and educational purposes.

Documentation with intuation, math formulation and necessary proofs are being made by the repo owner, will be ready to view shortly.

Required Packages

Numpy: Fundamental package for scientific computing with Python


Supervised learning

Linear Regression - Least Square Estimation - Done

Stepwise Regression - Done

Perceptron - Done

Logistic Regression - Done

K-Nearest-Neighbor - Done

NaiveBayes - Done

DecisionTree-ID3 - Done

DecisionTree-Pruning - ToDo

SVM - ToDo

AdaBoost - ToDo


Unsupervised learning

Principal Component Analysis - Done

K-means Clustering - Done

Hierarchical Clustering - Done

Gaussian Mixture Model - ToDo

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