Introduces feed-forward networks, covering neural network structure, training, activation functions, and optimization, with applications in forecasting and finance.
Explores classical vision theories, including Gestaltism, ecological approach, and constructivism, covering concepts like bottom-up vs. top-down processing.
Covers the use of transformers in robotics, focusing on embodied perception and innovative applications in humanoid locomotion and reinforcement learning.