R: Unleash Machine Learning Techniques

Find out how to build smarter machine learning systems with R. Follow this three module course to become a more fluent machine learning practitioner.

R: Unleash Machine Learning Techniques

Raghav Bali et al.

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Find out how to build smarter machine learning systems with R. Follow this three module course to become a more fluent machine learning practitioner.
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Book Details

ISBN 139781787127340
Paperback1123 pages

Book Description

R is the established language of data analysts and statisticians around the world. And you shouldn’t be afraid to use it…

This Learning Path will take you through the fundamentals of R and demonstrate how to use the language to solve a diverse range of challenges through machine learning. Accessible yet comprehensive, it provides you with everything you need to become more a more fluent data professional, and more confident with R.

In the first module you’ll get to grips with the fundamentals of R. This means you’ll be taking a look at some of the details of how the language works, before seeing how to put your knowledge into practice to build some simple machine learning projects that could prove useful for a range of real world problems.

For the following two modules we’ll begin to investigate machine learning algorithms in more detail. To build upon the basics, you’ll get to work on three different projects that will test your skills. Covering some of the most important algorithms and featuring some of the most popular R packages, they’re all focused on solving real problems in different areas, ranging from finance to social media.

This Learning Path has been curated from three Packt products:

Table of Contents

Chapter 22: Linear Regression – The Blocking and Tackling of Machine Learning
Chapter 25: More Classification Techniques – K-Nearest Neighbors and Support Vector Machines

What You Will Learn

  • Get to grips with R techniques to clean and prepare your data for analysis, and visualize your results
  • Implement R machine learning algorithms from scratch and be amazed to see the algorithms in action
  • Solve interesting real-world problems using machine learning and R as the journey unfolds
  • Write reusable code and build complete machine learning systems from the ground up
  • Learn specialized machine learning techniques for text mining, social network data, big data, and more
  • Discover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problems
  • Evaluate and improve the performance of machine learning models
  • Learn specialized machine learning techniques for text mining, social network data, big data, and more

Authors

Table of Contents

Chapter 22: Linear Regression – The Blocking and Tackling of Machine Learning
Chapter 25: More Classification Techniques – K-Nearest Neighbors and Support Vector Machines

Book Details

ISBN 139781787127340
Paperback1123 pages
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