Machine Learning by Stanford University at Coursera

Implementation of Machine Learning algorithms using MatLab.

This are my solutions to the course Machine Learning from Coursera by Prof. Andrew Ng

Working on identifying variance and bias

Course work for Machine Learning Course by Stanford University on Coursera

Here, we implement regularized linear regression to predict the amount of water flowing out of a dam using the change of water level in a reservoir. In the next half, we go through some diagnostics of debugging learning algorithms and examine the effects of bias v.s. variance.

Implementation of various Machine Learning (ML) Algorithms learned in the Machine Learning course authorised by Stanford University @ Coursera

Sequential adaptive elastic net (SAEN) approach, complex-valued LARS solver for weighted Lasso/elastic-net problems, and sparsity (or model) order detection with an application to single-snapshot source localization.

Andrew Ng's Machine Learning Course