If you enjoyed this book, you may be interested in these other books by Packt:

Machine Learning with R - Second Edition
Brett Lantz

ISBN: 978-1-78439-390-8

• Harness the power of R to build common machine learning algorithms with real-world data science applications
• Get to grips with R techniques to clean and prepare your data for analysis, and visualize your results
• Discover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problems
• Classify your data with Bayesian and nearest neighbor methods
• Predict values by using R to build decision trees, rules, and support vector machines
• Forecast numeric values with linear regression, and model your data with neural networks
• Evaluate and improve the performance of machine learning models
• Learn specialized machine learning techniques for text mining, social network data, big data, and more

Machine Learning with R Cookbook
Yu-Wei, Chiu (David Chiu)

ISBN: 978-1-78398-204-2

• Create and inspect the transaction dataset, performing association analysis with the Apriori algorithm
• Visualize patterns and associations using a range of graphs and find frequent itemsets using the Eclat algorithm
• Compare differences between each regression method to discover how they solve problems
• Predict possible churn users with the classification approach
• Implement the clustering method to segment customer data
• Compress images with the dimension reduction method
• Incorporate R and Hadoop to solve machine learning problems on big data