This is the code repository for Machine Learning with Go Quick Start Guide, published by Packt.
Hands-on techniques for building supervised and unsupervised machine learning workflows
Machine learning is an essential part of today's data-driven world and is extensively used across industries, including financial forecasting, robotics, and web technology. This book will teach you how to efficiently develop machine learning applications in Go.
This book covers the following exciting features:
- Manipulate string values and escape special characters
- Work with dates, times, maps, and arrays
- Handle errors and perform logging
- Explore files and directories
- Handle HTTP requests and responses
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
categories := []string{"tshirt", "trouser", "pullover", "dress", "coat",
"sandal", "shirt", "shoe", "bag", "boot"}
Following is what you need for this book: This book is for developers and data scientists with at least beginner-level knowledge of Go, and a vague idea of what types of problem Machine Learning aims to tackle. No advanced knowledge of Go (and no theoretical understanding of the math that underpins Machine Learning) is required.
With the following software and hardware list you can run all code files present in the book (Chapter 1-7).
| Chapter | Software required | OS required |
|---|---|---|
| 2-6 | Go | Ubuntu 16.04 server |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Michael Bironneau is an award-winning mathematician and experienced software engineer. He holds a PhD in mathematics from Loughborough University and has worked in several data science and software development roles. He is currently technical director of the energy AI technology company, Open Energi.
Toby Coleman is an experienced data science and machine learning practitioner. Following degrees from Cambridge University and Imperial College London, he has worked on the application of data science techniques in the banking and energy sectors. Recently, he held the position of innovation director at cleantech SME Open Energi, and currently provides machine learning consultancy to start-up businesses.
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Simply click on the link to claim your free PDF.