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)

Implementating the classifier

In the earlier parts of the chapter, we sketched out a dummy Classifier type that does nothing. Let's make it do something now:

type Classifier struct {
corpus *corpus.Corpus

tfidfs [MAXCLASS]*tfidf.TFIDF
totals [MAXCLASS]float64

ready bool
sync.Mutex
}

Here, there are introductions to a few things. Let's walk them through one by one:

  • We'll start with the corpus.Corpus type.
  • This is a type imported from the corpus package, which is a subpackage of the NLP library for Go, lingo.
  • To install lingo, simply run go get -u github.com/chewxy/lingo/....
  • To use the corpus package, simply import it like so: import "github.com/chewxy/lingo/corpus".
Bear in mind that in the near future, the package will change to github.com/go-nlp/lingo. If you are reading this after January 2019, use the new address.

A corpus.Corpus object simply...