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This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition
Machine Learning course offered by Stanford University at Coursera | Instructor: Andrew Ng
Machine Learning course that covers the most effective ML techniques, the theoretical underpinnings of learning, the practical knowledge needed to quickly and powerfully apply these techniques to new problems, and best practices in innovation as it pertains to machine learning and AI.
Face recognition with Bayesian Classifier, KNN, KernelSVM (Linear, RBF, Polynomial), Boosted SVM, PCA, LDA
This repository consists of my Matlab codes for ML algorithms implementations. It consists of various coding assignments done while attending ML course by Andrew Ng. It consists of vectorized implementation of various cost functions, optimizers, gradient updates and finding best parameters for the decision boundary.