Machine-Learning-for-Signal-Processing

This repository consists of work done in Machine Learning and Signal Processing.

Machine Learning Stage consists of:

• K-means
• Expectation Maximization
• Principal Component Analysis (PCA)
• Mixture Models
• Hidden Markov Models (HMM)
• Graphical Models * Gibbs Sampling
• Manifold Learning
• Hashing

Signal Processing Stage consists of:

• Source Separation
• Stereo Matching
• Audio Processing
• Fourier Transform
• Brain Waves
• Keyword Detection
• Sentiment Analysis
• Music Signal Processing
• Image Segmentation