Multilayer Neural Networks: Deep Learning

This lecture covers the fundamentals of multilayer neural networks and deep learning, focusing on topics such as neural network architecture, training processes, loss functions, and evaluation metrics. The instructor explains the concepts of forward and backward propagation, gradient descent optimization, and the importance of activation functions in improving model performance.