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


Clustering is the unsupervised version of classification where the grouping of data into categories is based on some metric of similarity or distance. This section will use k-means clustering, which is the most famous clustering technique and one that is also easy to implement. Once again, we are going to use an external library that can be found at

The utility that showcases clustering in Go is called cluster.go, and it is going to be presented in three parts. The utility requires one command-line argument, which is the number of clusters that are going to be created.

The first part of cluster.go is as follows:

package main 
import ( 
var observations []gokmeans.Node = []gokmeans.Node{