This course provides an overview of popular algorithms in machine learning. Topics include supervised and unsupervised learning, linear and polynomial regression, clustering, classification algorithms, gradient descent, support vector machines, decision trees, random forests, instance-based learning, neural networks, and genetic algorithms.