Machine Learning with R - Third Edition: Expert techniques for predictive modeling
Language: English
Published by Packt Publishing, 2019
- Softcover
- Used
Seller: Sugarhouse Book Works, LLC, Salt Lake City, UT, U.S.A.Sugarhouse Book Works, LLC
AbeBooks seller since March 25, 2022
Condition: Used - Very good
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As pictured. Very light edge wear. No marks throughout. Carefully packed and promptly shipped.
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- Title
- Machine Learning with R - Third Edition: Expert techniques for predictive modeling
- Author
- Lantz, Brett
- Publisher
- Packt Publishing
- Publication year
- 2019
- Condition
- VeryGood
- Binding
- paperback
- Language
- English
- ISBN 10
- 1788295862
- ISBN 13
- 9781788295864
- Edition
- 3rd Edition
- Item weight
- 30 ounces
- Dimensions
- 7x1x9
Solve real-world data problems with R and machine learning
Key Features:
- Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.6 and beyond
- Harness the power of R to build flexible, effective, and transparent machine learning models
- Learn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett Lantz
Book Description:
Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data.
Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings.
This new 3rd edition updates the classic R data science book to R 3.6 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R.
What You Will Learn:
- Discover the origins of machine learning and how exactly a computer learns by example
- Prepare your data for machine learning work with the R programming language
- Classify important outcomes using nearest neighbor and Bayesian methods
- Predict future events using decision trees, rules, and support vector machines
- Forecast numeric data and estimate financial values using regression methods
- Model complex processes with artificial neural networks - the basis of deep learning
- Avoid bias in machine learning models
- Evaluate your models and improve their performance
- Connect R to SQL databases and emerging big data technologies such as Spark, H2O, and TensorFlow
Who this book is for:
Data scientists, students, and other practitioners who want a clear, accessible guide to machine learning with R.
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
Sugarhouse Book Works, LLC
Salt Lake City, UT, U.S.A.
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