You're reading from Machine Learning with R Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data

Product type Paperback

Published in May 2023

Publisher Packt

ISBN-13 9781801071321

Length 762 pages

Edition 4th Edition

Languages

Tools

H2O

Concepts

Big Data

Author (1):

Brett Lantz

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Table of Contents (18) Chapters

Preface

1. Introducing Machine Learning

2. Managing and Understanding Data FREE CHAPTER

3. Lazy Learning – Classification Using Nearest Neighbors

4. Probabilistic Learning – Classification Using Naive Bayes

5. Divide and Conquer – Classification Using Decision Trees and Rules

6. Forecasting Numeric Data – Regression Methods

7. Black-Box Methods – Neural Networks and Support Vector Machines

8. Finding Patterns – Market Basket Analysis Using Association Rules

9. Finding Groups of Data – Clustering with k-means

10. Evaluating Model Performance

11. Being Successful with Machine Learning

12. Advanced Data Preparation

13. Challenging Data – Too Much, Too Little, Too Complex

14. Building Better Learners

15. Making Use of Big Data

16. Other Books You May Enjoy

17. Index

Making Use of Big Data

Although today’s most exciting machine learning research is found in the realm of big data—computer vision, natural language processing, autonomous vehicles, and so on—most business applications are much smaller scale, using what might be termed, at best, “medium” data. As noted in Chapter 12, Advanced Data Preparation, true big data work requires access to datasets and computing facilities generally found only at very large tech companies or research universities. Even then, the actual job of using these resources is often primarily a feat of data engineering, which simplifies the data greatly before its use in conventional business applications.

The good news is that the headline-making research conducted at big data companies eventually trickles down and can be applied in simpler forms to more traditional machine learning tasks. This chapter covers a variety of approaches for making use of such big data methods in R...

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You're reading from Machine Learning with R Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data

Table of Contents (18) Chapters

Making Use of Big Data

Authors (1)

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You're reading from Machine Learning with R Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data

Table of Contents (18) Chapters

Making Use of Big Data

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