Book Image

Go Machine Learning Projects

By : Xuanyi Chew
Book Image

Go Machine Learning Projects

By: Xuanyi Chew

Overview of this book

Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured. The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you'll learn how to choose the most appropriate machine learning algorithms to use for your projects with the help of a facial detection project. By the end of this book, you will have developed a solid machine learning mindset, a strong hold on the powerful Go toolkit, and a sound understanding of the practical implementations of machine learning algorithms in real-world projects.
Table of Contents (12 chapters)

Decomposing CO2 Trends Using Time Series Analysis

If you are reading this book in the year 2055—assuming you're still using a year system based on the Common Era (a year is the time taken by the planet you're on to go around the sun once)—congratulations! You have survived. This book is written in the year 2018, and we as humans have much to worry about in terms of the survival of our species.

By and large, we have managed to work our way into a relatively stable peace, but the future of our species as a whole is somewhat at risk from various threats. Most of these threats have been caused by our own actions in the past. I'd like to emphasize a point here: I'm not assigning blame to anyone in the past for causing these threats. Our ancestors were busy optimizing to different goals, and the threats are typically an unforeseen/unforeseeable side...