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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

Tour of Machine Learning Algorithms

In this chapter, we're going to explore the different ways to categorize the types of tasks that machine learning (ML) can accomplish, and categorize the ML algorithms themselves. There are many different ways to organize the ML landscape; we can categorize algorithms by the type of training data we give them, we can categorize by the type of output we expect from the algorithms, we can categorize algorithms by their specific methods and tactics, we can categorize them by the format of the data they work with, and so on.

As we discuss the different types and categories of ML tasks and algorithms throughout this chapter, we'll also introduce many of the algorithms that you'll encounter throughout this book. Only the high-level concepts of algorithms will be discussed in this chapter, allowing us to go into detail in later chapters...

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