Machine Learning with R: Learn How to Use R to Apply Powerful Machine Learning Methods and Gain and Insight into Real-world Applications

Lantz, Brett

ISBN 10: 1782162143 / ISBN 13: 9781782162148

Editore: Packt Pub Ltd, 2013

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Titolo: Machine Learning with R: Learn How to Use R ...

Casa editrice: Packt Pub Ltd

Data di pubblicazione: 2013

Legatura: paperback

Condizione: New

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Riassunto:

Machine learning, at its core, is concerned with transforming data into actionable knowledge. This fact makes machine learning well-suited to the present-day era of "big data" and "data science". Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning. Whether you are new to data science or a veteran, machine learning with R offers a powerful set of methods for quickly and easily gaining insight from your data.

"Machine Learning with R" is a practical tutorial that uses hands-on examples to step through real-world application of machine learning. Without shying away from the technical details, we will explore Machine Learning with R using clear and practical examples. Well-suited to machine learning beginners or those with experience. Explore R to find the answer to all of your questions.

How can we use machine learning to transform data into action? Using practical examples, we will explore how to prepare data for analysis, choose a machine learning method, and measure the success of the process.

We will learn how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data.

"Machine Learning with R" will provide you with the analytical tools you need to quickly gain insight from complex data.

L'autore:

Brett Lantz

Brett Lantz has spent the past 10 years using innovative data methods to understand human behavior. A sociologist by training, he was first enchanted by machine learning while studying a large database of teenagers' social networking website profiles. Since then, he has worked on interdisciplinary studies of cellular telephone calls, medical billing data, and philanthropic activity, among others. When he's not spending time with family, following college sports, or being entertained by his dachshunds, he maintains dataspelunking.com, a website dedicated to sharing knowledge about the search for insight in data.