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Deep Learning with Python
Contributor(s): Chollet, Francois (Author)

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ISBN: 1617294438     ISBN-13: 9781617294433
Publisher: Manning Publications
OUR PRICE: $47.49  

Binding Type: Paperback - See All Available Formats & Editions
Published: December 2017
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Temporarily out of stock - Will ship within 2 to 5 weeks
Additional Information
BISAC Categories:
- Computers | Programming Languages - Python
- Computers | Web - Search Engines
- Computers | Programming - General
Physical Information: 0.81" H x 7.38" W x 9.25" L (1.50 lbs) 384 pages
Features: Price on Product
 
Descriptions, Reviews, Etc.
Publisher Description:
Summary

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Fran ois Chollet, this book builds your understanding through intuitive explanations and practical examples.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Technology

Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning--a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications.

About the Book

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Fran ois Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.

What's Inside

  • Deep learning from first principles
  • Setting up your own deep-learning environment
  • Image-classification models
  • Deep learning for text and sequences
  • Neural style transfer, text generation, and image generation

About the Reader

Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required.

About the Author

Fran ois Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.

Table of Contents

    PART 1 - FUNDAMENTALS OF DEEP LEARNING
  1. What is deep learning?
  2. Before we begin: the mathematical building blocks of neural networks
  3. Getting started with neural networks
  4. Fundamentals of machine learning
  5. PART 2 - DEEP LEARNING IN PRACTICE
  6. Deep learning for computer vision
  7. Deep learning for text and sequences
  8. Advanced deep-learning best practices
  9. Generative deep learning
  10. Conclusions
  11. appendix A - Installing Keras and its dependencies on Ubuntuappendix B - Running Jupyter notebooks on an EC2 GPU instance

Contributor Bio(s): Chollet, Francois: -

Francois 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.


 
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