Go Machine Learning Projects

Exciting breakthrough projects to explore capabilities of GO and Machine Learning
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Go Machine Learning Projects

Xyanyi Chew

Exciting breakthrough projects to explore capabilities of GO and Machine Learning
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Book Details

ISBN 139781788993401
Paperback430 pages

Book Description

Go is the perfect language for machine learning as it is high level enough to describe complex algorithms and low level enough for the developer to develop an understanding that allows for efficient optimized code to be run. This book will teach you how to master machine learning on Go. The result would be programs that are easy to deploy, code that is easy to understand, and relatively easy to debug and measure performance.

You begin with setting up the Machine Learning environment with Go libraries and its capabilities. You will dive into regression analysis on a real-life data set on house pricing and then build a classification model in Go to classify emails as spam or ham. Using Gonum and Gorgonia, you will explore projects on Time series analysis along with decomposition, detect russian bots using clustering, social media analysis using ME model. Further, you will recognize handwriting using deep learning techniques such as neural networks and CNN. In the end, you will use GoCV and Gorgonia for facial recognition and then learn to choose best machine learning model using meta learning to Go data structures

Finally, the reader will have a solid machine learning mindset and a powerful Go toolkit of techniques, packages for practical implementations in real life projects.

Table of Contents

What You Will Learn

  • Demystify the Go machine learning landscape
  • Learn to use Gonum for regression and classification
  • Utilize times series models and decompose trends with powerful Go libraries 
  • Detect bots by implementing clustering algorithms in Go.
  • Build maximum entropy and random forest model for Sentiment Analysis
  • Recognise handwriting using neural networks and CNN with Gorgonia
  • Get to explore GoCV and OpenCv to implement facial recognition

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Table of Contents

Book Details

ISBN 139781788993401
Paperback430 pages
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