Description
Deep Learning With R is a practical guide to building deep learning models using the R programming language and the Keras library. Written by experts Francois Chollet, Tomasz Kalinowski, and J. J. Allaire, this book bridges the gap between deep learning theory and implementation.
The book covers essential deep learning concepts including neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs). Each chapter combines theoretical explanations with practical, reproducible code examples that readers can implement immediately. The authors demonstrate how to tackle real-world problems such as image classification, text analysis, and time series prediction.
Whether you’re a data scientist, statistician, or R programmer looking to enter the deep learning field, this book provides the foundation and practical skills needed to build, train, and deploy deep learning models effectively using R.
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