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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

The mathematical perspective

Association rule learning assumes that you have a transactional database to learn from. This doesn't refer to any specific technology, but rather the concept of a database that stores transactions—the database can be an array in memory, an Excel file, or a table in your production MySQL or PostgreSQL instance. Since association rule learning was developed for products in supermarkets, the original transactional database was a list of items bought by each individual shopper on a given shopping trip—essentially an archive of receipts from the checkout aisle. However, a transactional database can be any list of items or events that occur during a single session, whether that session is a shopping trip, a website visit, or a trip to a doctor. For the time being, we'll consider the supermarket example. We'll discuss other uses...

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