Practical machine learning
An online course with 10 lectures offering a practical introduction to machine learning,
including classification, regression, dimensionality
reduction and unsupervised learning. Topics covered include linear classification and regression, nearest neighbor methods, support
vector machines, decision trees, neural networks, clustering, and anomaly detection.