Convolutional Neural Networks: Fundamentals

This lecture covers the fundamentals of Convolutional Neural Networks (CNNs), including data statistics, training optimization, and the structure of CNN layers. Topics include neural network optimization, convolution definitions, gradient descent variants, and the importance of learning rates. The lecture also delves into the concept of pooling layers, feature engineering, and the potential pitfalls of relying solely on summary statistics.