Appendix 1. Other Books You May Enjoy

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 Cookbook Dr. PKS Prakash, Achyutuni Sri Krishna Rao

ISBN: 9781787121089

• Build deep learning models in different application areas using TensorFlow, H2O, and MXnet.
• Analyzing a Deep boltzmann machine
• Setting up and Analyzing Deep belief networks
• Building supervised model using various machine learning algorithms
• Set up variants of basic convolution function
• Represent data using Autoencoders.
• Explore generative models available in Deep Learning.
• Discover sequence modeling using Recurrent nets
• Learn fundamentals of Reinforcement Leaning
• Learn the steps involved in applying Deep Learning in text mining
• Explore application of deep learning in signal processing
• Utilize Transfer learning for utilizing pre-trained model
• Train a deep learning model on a GPU