Hands-On Deep Learning with Go

What this book covers

Chapter 1, Introduction to Deep Learning in Go, introduces the history and applications of deep learning. This chapter also gives an overview of ML with Go.

Chapter 2, What is a Neural Network and How Do I Train One?, covers how to build a simple neural network and how to inspect a graph, as well as many of the commonly used activation functions. This chapter also discusses some of the different options for gradient descent algorithms and optimizations for your neural network.

Chapter 3, Beyond Basic Neural Networks – Autoencoders and RBMs, shows how to build a simple multilayer neural network and an autoencoder. This chapter also explores the design and implementation of a probabilistic graphical model, an RBM, used ...