Machine Learning with TensorFlow Format: Paperback

Shukla, Nishant

ISBN 10: 1617293873 / ISBN 13: 9781617293870

Editore: Simon and Schuster, 2018

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Dati bibliografici

• Titolo: Machine Learning with TensorFlow Format: Paperback
• Editore: Simon and Schuster
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 1617293873
• ISBN 13: 9781617293870
• Rilegatura: Brossura
• Condizione: New

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Riassunto

Summary

Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python.

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

About the Technology

TensorFlow, Google's library for large-scale machine learning, simplifies often-complex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine.

About the Book

Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. You'll learn the basics by working with classic prediction, classification, and clustering algorithms. Then, you'll move on to the money chapters: exploration of deep-learning concepts like autoencoders, recurrent neural networks, and reinforcement learning. Digest this book and you will be ready to use TensorFlow for machine-learning and deep-learning applications of your own.

What's Inside

• Matching your tasks to the right machine-learning and deep-learning approaches
• Visualizing algorithms with TensorBoard
• Understanding and using neural networks

About the Reader

Written for developers experienced with Python and algebraic concepts like vectors and matrices.

About the Author

Author Nishant Shukla is a computer vision researcher focused on applying machine-learning techniques in robotics.

Senior technical editor, Kenneth Fricklas, is a seasoned developer, author, and machine-learning practitioner.

Table of Contents

PART 1 - YOUR MACHINE-LEARNING RIG

1. A machine-learning odyssey
2. TensorFlow essentials

PART 2 - CORE LEARNING ALGORITHMS

3. Linear regression and beyond
4. A gentle introduction to classification
5. Automatically clustering data
6. Hidden Markov models

PART 3 - THE NEURAL NETWORK PARADIGM

7. A peek into autoencoders
8. Reinforcement learning
9. Convolutional neural networks
10. Recurrent neural networks
11. Sequence-to-sequence models for chatbots
12. Utility landscape

Informazioni sugli autori

Nishant Shukla is a computer vision researcher at UCLA, focusing on machine learning techniques with robotics. He has been a developer for Microsoft, Facebook, and Foursquare, and a machine learning engineer for SpaceX, as well as the author of the Haskell Data Analysis Cookbook.

Nishant Shukla is a computer vision researcher at UCLA, focusing on machine learning techniques with robotics. He has been a developer for Microsoft, Facebook, and Foursquare, and a machine learning engineer for SpaceX, as well as the author of the Haskell Data Analysis Cookbook.