Deep Learning with Python

Deep Learning with Python
- Care instruction: Keep away from fire
- It can be used as a gift
- It is made up of premium quality material.
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 FranÂ§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 learningâ‚¬"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 FranÂ§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

FranÂ§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
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. Deep learning for computer vision
6. Deep learning for text and sequences
7. Advanced deep-learning best practices
8. Generative deep learning
9. Conclusions
10. appendix A - Installing Keras and its dependencies on Ubuntu
11. appendix B - Running Jupyter notebooks on an EC2 GPU instance
Country USA
Brand Manning Publications
Manufacturer Manning
Binding Paperback
ItemPartNumber YES39281977
ReleaseDate 2017-12-22
UnitCount 1
EANs 9781617294433

Deep Learning with Python

PART 1 - FUNDAMENTALS OF DEEP LEARNING

PART 2 - DEEP LEARNING IN PRACTICE

You might also like...

Country	USA
Brand	Manning Publications
Manufacturer	Manning
Binding	Paperback
ItemPartNumber	YES39281977
ReleaseDate	2017-12-22
UnitCount	1
EANs	9781617294433