Machine-Learning-Implementations

This Repository contains Implementation of Popular Machine Learning Algorithms in Python from Scratch

Anomaly Detection

Implement Anomaly Detection Algorithm to detect failing servers on a network.

K Means Clustering and Principal Component Analysis

Use Kmeans Clustering Algorithm to Compress an image. Use PCA to find low dimensional representation of face images.

Linear Regression

Use Linear Regression to Predict the price of Houses.

Logisitic Regression

Use Logisitic Regression to predict whether a students gets into the university or not.

Multi Class Classification

Use One-vs-All Logistic Regression to recognize hand written digits.

Neural Networks

Implement BackProp Algorithm on the classic MNIST Database.

Recommender Systems

Implement the Collaborative Filtering Learning Algorithm and apply it to a dataset of movie ratings to recommend movies to the user

Support Vector Machines

Use SVMs to build a spam classifer

Debugging a Learning Algorithm

Implement Regularized Linear Regression and use it to study models with different bias-variance properties