Understanding Machine Learning

This course systematically covers everything from the basic concepts of machine learning to its major algorithms. Starting with data representation, linear regression and classification, and optimization, it goes on to cover decision trees, ensembles, neural networks, unsupervised learning, and reinforcement learning. You will also learn about model generalization, selection, and interpretation, gaining an understanding of machine learning’s core principles and overall workflow.