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Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition - HHShop68
Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition - HHShop68
Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition - HHShop68
Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition - HHShop68
Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition - HHShop68
Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition - HHShop68
Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition - HHShop68
Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition - HHShop68

Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition - HHShop68

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Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition: 459 pages

Author : Brett Lantz

Language : English

1) 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.

2) About Author

Brett Lantz (@DataSpelunking) has spent more than 10 years using innovative data methods to understand human behavior. A sociologist by training, Brett was first captivated by machine learning during research on a large database of teenagers' social network profiles. Brett is a DataCamp instructor and a frequent speaker at machine learning conferences and workshops around the world. He is known to geek out about data science applications for sports, autonomous vehicles, foreign language learning, and fashion, among many other subjects, and hopes to one day blog about these subjects at Data Spelunking, a website dedicated to sharing knowledge about the search for insight in data.

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