Deep Learning: Technical Introduction

This book presents in a technical though hopefully pedagogical way the three most common forms of neural network architectures: Feedforward, Convolutional and Recurrent. For each network, their fundamental building blocks are detailed. The forward pass and the update rules for the backpropagation algorithm are then derived in full.

It could be the first stop for deep learning beginners, as it contains lots of concrete, easy-to-follow examples with corresponding tutorial videos and code notebooks.

The science behind deep learningBuilding and training your own neural networksPrivacy concepts, including federated learningTips for continuing your pursuit of deep learning