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.
Les mer
Expert Techniques for Predictive Modeling
Produktdetaljer
ISBN
9781788291552
Publisert
2019
Utgave
3. utgave
Utgiver
Packt Publishing
Språk
Product language
Engelsk
Format
Product format
Digital bok
Forfatter