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Hands-on Machine Learning with JavaScript

You're reading from   Hands-on Machine Learning with JavaScript Solve complex computational web problems using machine learning

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788998246
Length 356 pages
Edition 1st Edition
Languages
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Author (1):
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Burak Kanber Burak Kanber
Author Profile Icon Burak Kanber
Burak Kanber
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Table of Contents (14) Chapters Close

Preface 1. Exploring the Potential of JavaScript FREE CHAPTER 2. Data Exploration 3. Tour of Machine Learning Algorithms 4. Grouping with Clustering Algorithms 5. Classification Algorithms 6. Association Rule Algorithms 7. Forecasting with Regression Algorithms 8. Artificial Neural Network Algorithms 9. Deep Neural Networks 10. Natural Language Processing in Practice 11. Using Machine Learning in Real-Time Applications 12. Choosing the Best Algorithm for Your Application 13. Other Books You May Enjoy

Summary

In this chapter, we've discussed the important moments of JavaScript's history as applied to ML, starting from the launch of Google (https://www.google.com/) and finishing up at the end of 2017 with the release of Google's deeplearn.js library.

We’ve discussed some advantages to using JavaScript for machine learning, and also some of the challenges we’re facing, particularly in terms of the machine learning ecosystem.

We then took a tour of the most important recent developments in the JavaScript language, and had a brief introduction to ES6, the newest stable JavaScript language specification.

Finally, we set up an example development environment using Node.js, the Yarn package manager, Babel, and Browserify—tools that we will use throughout the rest of the book in our examples.

In the next chapter, we'll begin exploring and processing the data itself.

You have been reading a chapter from
Hands-on Machine Learning with JavaScript
Published in: May 2018
Publisher: Packt
ISBN-13: 9781788998246
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