Machine Learning with Go

Rahul Agrawal, Vipul Agrawal

nao informado

2017

355 páginas

11h 50m

ISBN-13: 9781785882104

Inglês

Get started with machine learning with Google's own Go languageAbout This Book* Build simplistic machine learning systems using popular machine libraries in the Go ecosystem* Learn about the statistics, algorithms, and tools needed to get up and running with machine learning in Go* Understand how to choose between machine learning models to solve problems at handWho This Book Is ForThis book is for Go developers who are familiar with syntax and programming with Go and now want to enter the field of data science with Go. Familiarity with statistics and math is necessary.What you will learn* Get a quick walkthrough of the basics of Machine Learning* Understand engineering issues-model size, prediction time, training time, and model updates* Understand SVM, decision trees, random forests, ensembles, and neural networks* Apply the knowledge gained to build actual systems and see how machine learning actually fits in end-to-end systems* Address practical issues when deploying a machine learning system in real-world scenariosIn DetailGo is getting more and more popular due to its simplicity. The sheer possibilities to perform machine learning with Go is exciting. This book will teach you how to perform the various aspects of machine learning tasks using Go.This book introduces you to the concepts of machine learning and will also help you understand the Go environment and set it up. You will gain hands-on experience of working with various machine learning algorithms such as clustering, naive bayes, random forest, SVM, decision trees, neural networks, factorization, and much more. You will learn to address practical issues when deploying a machine learning system through real-world scenarios. You will also get to grips with Convolutional Neural Networks to build an improved Wikipedia English Classifier.By the end of the book, you will have be able to apply all the knowledge gained to build actual systems and see how machine learning actually fits in end-to-end systems.