Book Image

Mastering Go - Second Edition

By : Mihalis Tsoukalos
Book Image

Mastering Go - Second Edition

By: Mihalis Tsoukalos

Overview of this book

Often referred to (incorrectly) as Golang, Go is the high-performance systems language of the future. Mastering Go, Second Edition helps you become a productive expert Go programmer, building and improving on the groundbreaking first edition. Mastering Go, Second Edition shows how to put Go to work on real production systems. For programmers who already know the Go language basics, this book provides examples, patterns, and clear explanations to help you deeply understand Go’s capabilities and apply them in your programming work. The book covers the nuances of Go, with in-depth guides on types and structures, packages, concurrency, network programming, compiler design, optimization, and more. Each chapter ends with exercises and resources to fully embed your new knowledge. This second edition includes a completely new chapter on machine learning in Go, guiding you from the foundation statistics techniques through simple regression and clustering to classification, neural networks, and anomaly detection. Other chapters are expanded to cover using Go with Docker and Kubernetes, Git, WebAssembly, JSON, and more. If you take the Go programming language seriously, the second edition of this book is an essential guide on expert techniques.
Table of Contents (20 chapters)
Title Page

Working with TensorFlow

TensorFlow is a rather famous open-source platform for machine learning. In order to use TensorFlow with Go, you will first need to download a Go package:

$ go get

However, for the aforementioned command to work, the C interface for TensorFlow should be already installed. On a macOS Mojave machine, this can be installed as follows:

$ brew install tensorflow

If the C interface is not installed, and you try to install the Go package for TensorFlow, you will get the following error message:

$ go get
ld: library not found for -ltensorflow
clang: error: linker command failed with exit code 1 (use -v to see invocation)

As TensorFlow is pretty complex, it would be good to execute the following command in order to...