Sinossi
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Hardcover. Condizione: new. Hardcover. Ready to bring R code into the AI era? Stop switching languages. Build deep learning models in pure R. Master GPT-style transformers and diffusion. Skip complex math. Launch production-ready solutions confidently. Keras 3 interface: Code modern neural networks with the simplicity R users love. Vision, text, and time series: Apply models that classify images, translate text, and predict demand. Transformers and LLMs: Generate fluent language and summaries without Python detours. Diffusion imagery: Create new pictures and explore generative art inside RStudio. Scaling and tuning: Fine-tune hyperparameters for faster training and top-tier accuracy. Interpretability tools: Explain model decisions to bosses, regulators, and stakeholders. Deep Learning with R, Third Edition pairs Keras creator Francois Chollet with R expert Tomasz Kalinowski to deliver an authoritative guide. Step-by-step chapters move from first principles to advanced projects. Clear code, concise explanations, and runnable notebooks keep learning practical. New coverage of transformers, diffusion, and GPT-style language models brings bleeding-edge AI to R. By books end, you will design, train, and deploy high-performing models, interpret their outputs, and scale them for production. Your R workflow becomes an AI powerhouse. Ideal for data scientists and analysts with intermediate R skills who crave modern deep learning capabilities. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781633435186
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Hardback. Condizione: New. Ready to bring R code into the AI era? Stop switching languages. Build deep learning models in pure R. Master GPT-style transformers and diffusion. Skip complex math. Launch production-ready solutions confidently. Keras 3 interface: Code modern neural networks with the simplicity R users love. Vision, text, and time series: Apply models that classify images, translate text, and predict demand. Transformers and LLMs: Generate fluent language and summaries without Python detours. Diffusion imagery: Create new pictures and explore generative art inside RStudio. Scaling and tuning: Fine-tune hyperparameters for faster training and top-tier accuracy. Interpretability tools: Explain model decisions to bosses, regulators, and stakeholders. Deep Learning with R, Third Edition pairs Keras creator François Chollet with R expert Tomasz Kalinowski to deliver an authoritative guide. Step-by-step chapters move from first principles to advanced projects. Clear code, concise explanations, and runnable notebooks keep learning practical. New coverage of transformers, diffusion, and GPT-style language models brings bleeding-edge AI to R. By book's end, you will design, train, and deploy high-performing models, interpret their outputs, and scale them for production. Your R workflow becomes an AI powerhouse. Ideal for data scientists and analysts with intermediate R skills who crave modern deep learning capabilities. Codice articolo LU-9781633435186
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