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Deep Learning with R, Third Edition
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Deep Learning with R, Third Edition

Book Details

Format Hardback or Cased Book
ISBN-10 1633435180
ISBN-13 9781633435186
Publisher Manning Publications
Imprint Manning Publications
Country of Manufacture GB
Country of Publication GB
Publication Date Jun 6th, 2026
Print length 648 Pages
Weight 1,168 grams
Dimensions 23.50 x 18.80 x 4.00 cms
Ksh 11,200.00
Publisher Out of Stock 0 in stock

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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.

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. 


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