What this book covers
Chapter 1, Machine Learning Basics, reviews all the essential elements of machine learning. This quick refresher is important as we move into deep learning, a subset of machine learning, which shares a number of common terms and methods.
Chapter 2, Setting Up R for Deep Learning, summarizes the common frameworks and algorithms for deep learning and reinforced deep learning in R. You will become familiar with the common libraries, including MXNet, H2O, and Keras, and learn how to install each library in R.
Chapter 3, Artificial Neural Networks, teaches you about artificial neural networks, which make up the base building block for all deep learning. You will build a simple artificial neural network and learn how all of ...
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