Book Image

Hands-On Deep Learning with Go

By : Gareth Seneque, Darrell Chua
Book Image

Hands-On Deep Learning with Go

By: Gareth Seneque, Darrell Chua

Overview of this book

Go is an open source programming language designed by Google for handling large-scale projects efficiently. The Go ecosystem comprises some really powerful deep learning tools such as DQN and CUDA. With this book, you'll be able to use these tools to train and deploy scalable deep learning models from scratch. This deep learning book begins by introducing you to a variety of tools and libraries available in Go. It then takes you through building neural networks, including activation functions and the learning algorithms that make neural networks tick. In addition to this, you'll learn how to build advanced architectures such as autoencoders, restricted Boltzmann machines (RBMs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and more. You'll also understand how you can scale model deployments on the AWS cloud infrastructure for training and inference. By the end of this book, you'll have mastered the art of building, training, and deploying deep learning models in Go to solve real-world problems.
Table of Contents (15 chapters)
Free Chapter
1
Section 1: Deep Learning in Go, Neural Networks, and How to Train Them
6
Section 2: Implementing Deep Neural Network Architectures
11
Section 3: Pipeline, Deployment, and Beyond!

Loading data – MNIST

Before we can even begin to train or build our model, we first need to get some data. As it turns out, a lot of people have made data available online for us to use for this purpose. One of the best-curated datasets around is MNIST, which we will use for the first two examples in this chapter.

We'll learn how to download MNIST and load it into our Go program so that we can use it in our model.

What is MNIST?

Throughout this chapter, we're going to make use of a popular dataset called the MNIST database. This has been made available by Yann LeCun, Corinna Cortes, and Christopher Burges at http://yann.lecun.com/exdb/mnist.

The database gets its name from the fact that it was made by mixing...