This book provides a hands-on, readable guide to applying machine learning to real-world problems. Aimed at both experienced R users and developers new to the language, author Brett Lantz covers the topics needed to uncover key insights, make new predictions, and visualize data findings. This new 3rd edition updates the classic R data science book with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning.

<ASIN:1788295862>

Author: Brett Lantz
Publisher: Packt Publishing
Date: April 2019
Pages: 458
ISBN: 978-1788295864
Print: 1788295862
Kindle: B07PYXX3H5
Audience: R developers interested in machine learning
Level: Intermediate
Category: Artificial Intelligence

• 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

For more Book Watch just click.

Book Watch is I Programmer's listing of new books and is compiled using publishers' publicity material. It is not to be read as a review where we provide an independent assessment. Some, but by no means all, of the books in Book Watch are eventually reviewed.

To have new titles included in Book Watch contact  BookWatch@i-programmer.info

Follow @bookwatchiprog on Twitter or subscribe to I Programmer's Books RSS feed for each day's new addition to Book Watch and for new reviews.