Machine Learning With Tensorflow - Brossura

Shukla, Nishant

 
9781617293870: Machine Learning With Tensorflow
Brossura
ISBN 10: 1617293873 ISBN 13: 9781617293870
Casa editrice: Manning Pubns Co, 2018

Sinossi

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

    3. PART 2 - CORE LEARNING ALGORITHMS

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

    7. 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

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Manning Pubns Co
Data di pubblicazione
2018
Lingua
Inglese
ISBN 10 
1617293873
ISBN 13 
9781617293870
Rilegatura
Copertina flessibile
Numero edizione
1
Numero di pagine
251
Redattore
Fricklas Kenneth
Contatto del produttore
non disponibile
Persona responsabile
Simon and Schuster Netherlands BV, GPSR Europäische Union
info@simonandschuster.nl

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AA Utrecht
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