Advanced Deep Learning with Python

Preface

This book is a collection of newly evolved deep learning models, methodologies, and implementations based on the areas of their application. In the first section of the book, you will learn about the building blocks of deep learning and the math behind neural networks (NNs). In the second section, you'll focus on convolutional neural networks (CNNs) and their advanced applications in computer vision (CV). You'll learn to apply the most popular CNN architectures in object detection and image segmentation. Finally, you'll discuss variational autoencoders and generative adversarial networks. In the third section, you'll focus on natural language and sequence processing. You'll use NNs to extract sophisticated vector representations ...