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  3. Machine learning

Deep Learning with R, Second Edition

Af: Francois Chollet, Joseph Allaire, Tomasz Kalinowski Engelsk Paperback

Deep Learning with R, Second Edition

Af: Francois Chollet, Joseph Allaire, Tomasz Kalinowski Engelsk Paperback
Tjek vores konkurrenters priser
Deep learning from the ground up using R and the powerful Keras library!

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

  • Deep learning from first principles
  • Image classification and image segmentation
  • Time series forecasting
  • Text classification and machine translation
  • Text generation, neural style transfer, and image generation
Deep Learning with R, Second Edition  shows you how to put deep learning into action. It''s based on the revised new edition of François Chollet''s bestselling   Deep Learning with Python. All code and examples have been expertly translated to the R language by Tomasz Kalinowski, who maintains the Keras and Tensorflow R packages at RStudio. Novices and experienced ML practitioners will love the expert insights, practical techniques, and important theory for building neural networks.

about the technology

Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow put deep learning within reach for all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started on core DL tasks like computer vision, natural language processing, and more using R.

what''s inside

  • Image classification and image segmentation
  • Time series forecasting
  • Text classification and machine translation
  • Text generation, neural style transfer, and image generation

about the reader

For readers with intermediate R skills. No previous experience with Keras, TensorFlow, or deep learning is required.
 
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Tjek vores konkurrenters priser
Normalpris
kr 488
Fragt: 39 kr
6 - 8 hverdage
20 kr
Pakkegebyr
God 4 anmeldelser på
Tjek vores konkurrenters priser
Deep learning from the ground up using R and the powerful Keras library!

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

  • Deep learning from first principles
  • Image classification and image segmentation
  • Time series forecasting
  • Text classification and machine translation
  • Text generation, neural style transfer, and image generation
Deep Learning with R, Second Edition  shows you how to put deep learning into action. It''s based on the revised new edition of François Chollet''s bestselling   Deep Learning with Python. All code and examples have been expertly translated to the R language by Tomasz Kalinowski, who maintains the Keras and Tensorflow R packages at RStudio. Novices and experienced ML practitioners will love the expert insights, practical techniques, and important theory for building neural networks.

about the technology

Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow put deep learning within reach for all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started on core DL tasks like computer vision, natural language processing, and more using R.

what''s inside

  • Image classification and image segmentation
  • Time series forecasting
  • Text classification and machine translation
  • Text generation, neural style transfer, and image generation

about the reader

For readers with intermediate R skills. No previous experience with Keras, TensorFlow, or deep learning is required.
 
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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 568
ISBN-13: 9781633439849
Indbinding: Paperback
Udgave: 2
ISBN-10: 1633439844
Kategori: Machine learning
Udg. Dato: 3 aug 2022
Længde: 39mm
Bredde: 235mm
Højde: 190mm
Forlag: Manning Publications
Oplagsdato: 3 aug 2022
Forfatter(e): Francois Chollet, Joseph Allaire, Tomasz Kalinowski
Forfatter(e) Francois Chollet, Joseph Allaire, Tomasz Kalinowski

Kategori Machine learning

ISBN-13 9781633439849

Sprog Engelsk

Indbinding Paperback

Sider 568

Udgave 2

Længde 39mm

Bredde 235mm

Højde 190mm

Udg. Dato 3 aug 2022

Oplagsdato 3 aug 2022

Forlag Manning Publications

Kategori sammenhænge