Build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R
Key Features
- Harness the power of R for statistical computing and data science
- Explore, forecast, and classify data with R
- Use R to apply common machine learning algorithms to real-world scenarios
Book Description
Machine learning, at its core, is concerned with transforming data into actionable knowledge. This makes machine learning well suited to the present-day era of big data. Given the growing prominence of R’s cross-platform, zero-cost statistical programming environment, there has never been a better time to start applying machine learning to your data. Machine learning with R offers a powerful set of methods to quickly and easily gain insight from your data to both, veterans and beginners in data analytics.
Want to turn your data into actionable knowledge, predict outcomes that make real impact, and have constantly developing insights? R gives you access to all the power you need to master exceptional machine learning techniques.
The second edition of Machine Learning with R provides you with an introduction to the essential skills required in data science. Without shying away from technical theory, it is written to provide focused and practical knowledge to get you building algorithms and crunching your data, with minimal previous experience.
With this book, you’ll discover all the analytical tools you need to gain insights from complex data and learn to to choose the correct algorithm for your specific needs. Through full engagement with the sort of real-world problems data-wranglers face, you’ll learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, market analysis, and clustering. Transform the way you think about data; discover machine learning with R.
What you will learn
- Harness the power of
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