Deep Learning with R, Third Edition introduces R programmers to the latest advances in deep learning. In it, you’ll explore how to use Keras 3 and R to build and train deep learning models, all without advanced math or low-level programming. You’ll get started on core DL tasks like computer vision and natural language processing, and you’ll take your first steps into the world of transformers, LLMs, and the foundations of modern AI.
You’ll learn to fine-tune and evaluate your models for peak performance, and dive into advanced methods like transfer learning and model interpretability. This expanded third edition brings cutting-edge coverage of transformers, building your own GPT-style language model, and creating images with diffusion models—all in R.
Deep Learning with R, Second Edition is a hands-on guide to deep learning using the R language. As you move through this book, you’ll quickly lock in the foundational ideas of deep learning. The intuitive explanations, crisp illustrations, and clear examples guide you through core DL skills like image processing and text manipulation, and even advanced features like transformers. This revised and expanded new edition is adapted from Deep Learning with Python, Second Edition by François Chollet, the creator of the Keras library.