Yusuf Adekunle & Priya Mehta · 312 pages · Uploaded Sep 25, 2026
Introduction to Neural Networks
Backpropagation & Gradient Descent
Convolutional Neural Networks
Recurrent Networks & LSTMs
Attention & Transformers
Generative Adversarial Networks
Reinforcement Learning Fundamentals
Deploying Models at Scale
Explains convolutions, pooling layers, receptive fields, and famous architectures like VGG…
Explains convolutions, pooling layers, receptive fields, and famous architectures like VGG, ResNet, and EfficientNet.