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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

Most of this book has focused on the implementation of ML algorithms used to solve specific problems. However, the implementation of an algorithm is only one part of the software-engineering design process. An engineer must also be skilled in choosing the right algorithm or system for her problem and be able to debug issues as they arise.

In this chapter, you learned a simple four-point decision-making process that can help you choose the best algorithm or algorithms for a specific use case. Using the process of elimination, you can progressively reduce your options by disqualifying algorithms based on each of those decision points. Most obviously, you should not use an unsupervised algorithm when you're facing a supervised learning problem. You can further eliminate options by considering the specific task at hand or business goal, considering the format and form...

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