Book Image

Machine Learning with R - Third Edition

By : Brett Lantz
Book Image

Machine Learning with R - Third Edition

By: Brett Lantz

Overview of this book

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.
Table of Contents (18 chapters)
Machine Learning with R - Third Edition
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Working with online data and services

With growing amounts of data available from web-based sources, it is increasingly important for machine learning projects to be able to access and interact with online services. R is able to read data from online sources natively, with some caveats. First, by default, R cannot access secure websites (those using https:// rather than the http:// protocol). Secondly, it is important to note that most web pages do not provide data in a form that R can understand. The data will need to be parsed, or broken apart and rebuilt into a structured form before it can be useful. We'll discuss the workarounds shortly.

However, if neither of these caveats apply, that is, if the data are already online in a non-secure website and in a tabular form like CSV that R can understand natively, then R's read.csv() and read.table() functions can access it from the web just as if it were on your local machine. Simply supply the full Uniform Resource Locator (URL) for the dataset...