Nonlinear Supervised LearningExplores the inductive bias of different nonlinear supervised learning methods and the challenges of hyper-parameter tuning.
Neural Networks OptimizationExplores neural networks optimization, including backpropagation, batch normalization, weight initialization, and hyperparameter search strategies.
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.
Introduction to Data ScienceIntroduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
