Neural Networks: Multilayer PerceptronsCovers Multilayer Perceptrons, artificial neurons, activation functions, matrix notation, flexibility, regularization, regression, and classification tasks.
Neural Networks OptimizationExplores neural networks optimization, including backpropagation, batch normalization, weight initialization, and hyperparameter search strategies.
Nonlinear Supervised LearningExplores the inductive bias of different nonlinear supervised learning methods and the challenges of hyper-parameter tuning.
Hierarchical Control in RoboticsExplores hierarchical control concepts in robotics, including switching, prioritizing, and information chains, to achieve complex robot behaviors.
Obstacle Avoidance with DSExplores obstacle avoidance using Dynamical Systems for robots, focusing on modulation, stability guarantees, and contraction theory.
Deep Learning FundamentalsIntroduces deep learning, from logistic regression to neural networks, emphasizing the need for handling non-linearly separable data.
