Reinforcement Learning ConceptsCovers key concepts in reinforcement learning, neural networks, clustering, and unsupervised learning, emphasizing their applications and challenges.
Financial Time Series AnalysisCovers stylized facts of asset returns, summary statistics, testing for normality, Q-Q plots, and efficient market hypothesis.
Nonlinear Supervised LearningExplores the inductive bias of different nonlinear supervised learning methods and the challenges of hyper-parameter tuning.
Machine Learning FundamentalsIntroduces the basics of machine learning, covering supervised classification, logistic regression, and maximizing the margin.
