Neural Networks: Multilayer LearningCovers the fundamentals of multilayer neural networks and deep learning, including back-propagation and network architectures like LeNet, AlexNet, and VGG-16.
Vision-Language-Action Models: Training and ApplicationsDelves into training and applications of Vision-Language-Action models, emphasizing large language models' role in robotic control and the transfer of web knowledge. Results from experiments and future research directions are highlighted.
Supervised Learning OverviewCovers CNNs, RNNs, SVMs, and supervised learning methods, emphasizing the importance of tuning regularization and making informed decisions in machine learning.
Nonlinear Supervised LearningExplores the inductive bias of different nonlinear supervised learning methods and the challenges of hyper-parameter tuning.
