Neural Networks Explained: Building Blocks of Deep Learning

Neural Networks are the foundation of modern deep learning and AI. This detailed guide explains how neural networks work, from basic neurons and activation functions to advanced architectures like CNNs, RNNs, Transformers, and GANs. Learn about forward propagation, backpropagation, optimization algorithms like Adam, and essential training techniques including regularization, batch normalization, and transfer learning. Master the fundamentals needed to build and train effective deep learning models.