Various machine learning projects using public datasets

• Classification using Naive Bayes and Nearest Neighbours
• Support Vector Machine (SVM)
• Classification using Random Forest
• High Dimentional Data - Principal Component Analysis
• Clustering
• Regression
• Generalized Linear Models
• Boltzmman Machine Models
• Markov Chains and Hidden Markov Models
• Neural Networks
• Clustering using Expectation Maximization Algorithm - Image processing

• Boltzmman Machine Models - Image Processing
• Deep Learning using Tensorflow

• Time Series Analysis
• Sentiment Analysis
• Classification using Tree Based Models (XGBoost)
• Regression Using Tree Based Models (GBM)