Deep Learning with R, Third Edition

Tomasz Kalinowski

ISBN 10: 1633435180 / ISBN 13: 9781633435186

Editore: Manning Publications Jun 2026, 2026

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Neuware - Get the Elektronisches Buch free when you register your print book at Manning.This book introduces deep learning from scratch with examples that use the R language and the Keras library. Each chapter offers practical code examples that build your understanding of deep learning layer by layer. You ll appreciate the intuitive explanations, crisp illustrations, and clear examples. In this expanded third edition you ll find fresh chapters on the transformers architecture, building your own GPT-like large language model, and image generation with diffusion models. Plus, even DL veterans will benefit from the insightful explanations on the nature of deep learning. For R programmers, the R interface to the Keras deep learning library is a powerful head start on building deep learning models without switching to Python. It provides a simple, consistent API that makes deep learning accessible and simplifies the process of building neural networks, even if you have no prior experience in advanced machine learning. In Deep Learning with R, Third Edition you will learn: Deep learning from first principles The latest features of Keras Image classification and image segmentation Time series forecasting Text classification and machine translation Text and image generation build your own LLMs and diffusion models! Scaling and tuning models About the technology Deep Learning with R, Third Edition is a practical, concept-driven introduction to modern deep learning for R users. With a focus on clarity, intuition, and hands-on experimentation, it guides you from the foundations of deep learning to advanced architectures such as transformers and LLMs. This book treats R as a fully capable environment for modern deep learning, showing how contemporary models and workflows can be developed end to end without compromise. About the book Deep Learning with R, Third Edition gets you up to speed with the current state of deep learning practice. Using Keras 3 with R, you ll build and train neural networks from scratch, work with transformers, fine-tune pretrained models and explore large language models and diffusion-based image generation. By following carefully constructed examples that build insight step-by-step, you ll develop a deep understanding of why these models work not just how to use them. What's inside Hands-on, code-first learning in R A clear progression from deep learning fundamentals to generative AI Examples that emphasize intuition and understanding About the reader For readers with intermediate R skills. No prior experience with deep learning is required. About the author François Chollet is the creator of Keras and author of Deep Learning with Python. Tomasz Kalinowski is a software engineer at Posit Software, PBC and maintainer of the Keras and TensorFlow R packages. Table of Contents 1 What is deep learning 2 The mathematical building blocks of neural networks 3 Introduction to TensorFlow, PyTorch, JAX, and Keras 4 Classification and regression 5 Fundamentals of machine learning 6 The universal workflow of machine learning 7 A deep dive into Keras 8 Image classification 9 Convnet architecture patterns 10 Interpreting what convnets learn 11 Image segmentation 12 Object detection 13 Timeseries forecasting 14 Text classification 15 Language models and the Transformer 16 Text generation 17 Image generation 18 Best practices for the real world 19 The future of AI 20 Conclusions.

Codice articolo 9781633435186

Dati bibliografici

• Titolo: Deep Learning with R, Third Edition
• Editore: Manning Publications Jun 2026
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 10: 1633435180
• ISBN 13: 9781633435186
• Rilegatura: Buch
• Edizione: terza edizione
• Condizione: Neu
• Dimensioni: 233 L x 187 A x 48 P (millimetri) 233 millimetri di larghezza per 187 millimetri di altezza per 48 millimetri di profondità
• Peso: 878 grammi

Descrizione articolo

Riassunto

Deep learning from the ground up using R and the powerful Keras library!

Deep Learning with R, Third Edition introduces deep learning from scratch with examples that use the R language and the Keras library. Each chapter offers practical code examples that build your understanding of deep learning layer by layer. You’ll appreciate the intuitive explanations, crisp illustrations, and clear examples. In this expanded third edition you’ll find fresh chapters on the transformers architecture, building your own GPT-like large language model, and image generation with diffusion models. Plus, even DL veterans will benefit from the insightful explanations on the nature of deep learning.

In Deep Learning with R, Third Edition you will learn:

• Deep learning from first principles
• The latest features of Keras
• Image classification and image segmentation
• Time series forecasting
• Text classification and machine translation
• Text and image generation—build your own LLMs and diffusion models!
• Scaling and tuning models

For R programmers, the R interface to the Keras deep learning library is a powerful head start on building deep learning models without switching to Python. It provides a simple, consistent API that makes deep learning accessible and simplifies the process of building neural networks, even if you have no prior experience in advanced machine learning.

About the book

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.

About the reader

For readers with intermediate R skills. No previous experience with Keras, TensorFlow, Jax, Torch, or deep learning is required.

About the author

François Chollet is the creator of Keras. Tomasz Kalinowski is a software engineer at Posit Software, PBC (formerly RStudio) and maintainer of the Keras and Tensorflow R packages.

Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.

Informazioni sull?autore

François Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural networks since 2012. Francois is currently doing deep learning research at Google. He blogs about deep learning at blog.keras.io.

Tomasz Kalinowski is a software engineer at RStudio and maintainer of the Keras and Tensorflow R packages.