Explains the learning process in multi-layer neural networks, including back-propagation, activation functions, weights update, and error backpropagation.
Explores deep learning for autonomous vehicles, covering perception, action, and social forecasting in the context of sensor technologies and ethical considerations.
Introduces convolutional neural networks for image processing, covering basic components, architectures, and practical applications, including denoising and segmentation.
