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

R Deep Learning Essentials
Dr. Joshua F. Wiley

ISBN: 978-1-78528-058-0

• Set up the R package H2O to train deep learning models
• Understand the core concepts behind deep learning models
• Use Autoencoders to identify anomalous data or outliers
• Predict or classify data automatically using deep neural networks
• Build generalizable models using regularization to avoid overfitting the training data