Advanced Algorithms for Machine Learning

1 Unit · Graduate

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The remaining material covers algorithms for federated learning including differential privacy concepts, and autoML algorithms based on Bayesian optimization, genetic programming, and hyperband. Development in python and tensorflow is required. Reserved for graduate students.