My projects from the Stanford Machine Learning course offered on Coursera by Professor Andrew Ng.

Machine Learning Exercises

SVMs from scratch

Implementation of Supervised Learning Algorithms for different data sets.1)Amazon Baby Products Review Data-Set 2) Diabetic Readmission Data 3) Handwritten Digit Dataset

This is the page for the book Digital Signal Processing with Kernel Methods.

ML classifier for identifying encrypted streaming video traffic.

Feature Selection Based on Mutual Information Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy on Arrhythmia Dataset

This repositories contains implementation of various Machine Learning Algorithms such as Bayesian Classifier, Principal Component Analysis, Fisher Linear Discriminator, Face Recognition and Reconstruction, Gaussian Mixture Model based Segmentation, Otsu's Segmentation, Neural Network etc. Relevant data sets and results are also included.

Machine Learning Algorithms for the programming tasks of Stanford online course from Andrew Ng on Coursera

MATLAB Implementation of the SVM and Eigenface/Fishcerface Algorithms for Facial Recognition.

Machine Learning using Matlab

Machine Learning with MATLAB

Machine Learning principles in Octave/Matlab from Andrew Ng Specialization

Solutions for Coursera Machine Learning week 7 assignments

Using ε-Support Vector Regression (ε-SVR) for identification of Linear Parameter Varying (LPV) dynamical systems

machine-learning octave neural-networks linear-regression logistic-regression multi-class-classification support-vector-machines k-means-clustering principal-component-analysis anomaly-detection recommender-systems

Spam Classifier for emails using SVM

Image Inpainting using Chess Piece Vision LS-SVM

Machine learning ( RNN (Recurrent Neural Network) and SVM (Support Vector Machine) ) recognition/classification of 7 hand gestures using 6 channels of BioRadio 150 & BioCapture