Building Blocks - Linear Layers

Explore the fundamental building blocks of neural networks in this 59-minute lecture focusing on linear layers. Gain a comprehensive understanding of how these essential components function within deep learning architectures. Delve into the mathematical principles behind linear transformations and their role in processing input data. Learn about weight matrices, bias vectors, and activation functions that form the core of linear layers. Discover how these layers contribute to the overall structure and capabilities of neural networks. Enhance your knowledge of deep learning concepts and improve your ability to design and implement effective neural network models.