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  • TensorFlow in Action

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TensorFlow in Action

by Thushan Ganegedara (Author)
4.3 out of 5 stars (13)
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Unlock the TensorFlow design secrets behind successful deep learning applications! Deep learning StackOverflow contributor Thushan Ganegedara teaches you the new features of TensorFlow 2 in this hands-on guide.

In TensorFlow in Action you will learn:

Fundamentals of TensorFlow
Implementing deep learning networks
Picking a high-level Keras API for model building with confidence
Writing comprehensive end-to-end data pipelines
Building models for computer vision and natural language processing
Utilizing pretrained NLP models
Recent algorithms including transformers, attention models, and ElMo

In TensorFlow in Action, you'll dig into the newest version of Google's amazing TensorFlow framework as you learn to create incredible deep learning applications. Author Thushan Ganegedara uses quirky stories, practical examples, and behind-the-scenes explanations to demystify concepts otherwise trapped in dense academic papers. As you dive into modern deep learning techniques like transformer and attention models, you’ll benefit from the unique insights of a top StackOverflow contributor for deep learning and NLP.

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

About the technology
Google’s TensorFlow framework sits at the heart of modern deep learning. Boasting practical features like multi-GPU support, network data visualization, and easy production pipelines using TensorFlow Extended (TFX), TensorFlow provides the most efficient path to professional AI applications. And the Keras library, fully integrated into TensorFlow 2, makes it a snap to build and train even complex models for vision, language, and more.

About the book
TensorFlow in Action teaches you to construct, train, and deploy deep learning models using TensorFlow 2. In this practical tutorial, you’ll build reusable skill hands-on as you create production-ready applications such as a French-to-English translator and a neural network that can write fiction. You’ll appreciate the in-depth explanations that go from DL basics to advanced applications in NLP, image processing, and MLOps, complete with important details that you’ll return to reference over and over.

What's inside

Covers TensorFlow 2.9
Recent algorithms including transformers, attention models, and ElMo
Build on pretrained models
Writing end-to-end data pipelines with TFX

About the reader
For Python programmers with basic deep learning skills.

About the author
Thushan Ganegedara is a senior ML engineer at Canva and TensorFlow expert. He holds a PhD in machine learning from the University of Sydney.

Table of Contents
PART 1 FOUNDATIONS OF TENSORFLOW 2 AND DEEP LEARNING
1 The amazing world of TensorFlow
2 TensorFlow 2
3 Keras and data retrieval in TensorFlow 2
4 Dipping toes in deep learning
5 State-of-the-art in deep learning: Transformers
PART 2 LOOK MA, NO HANDS! DEEP NETWORKS IN THE REAL WORLD
6 Teaching machines to see: Image classification with CNNs
7 Teaching machines to see better: Improving CNNs and making them confess
8 Telling things apart: Image segmentation
9 Natural language processing with TensorFlow: Sentiment analysis
10 Natural language processing with TensorFlow: Language modeling
PART 3 ADVANCED DEEP NETWORKS FOR COMPLEX PROBLEMS
11 Sequence-to-sequence learning: Part 1
12 Sequence-to-sequence learning: Part 2
13 Transformers
14 TensorBoard: Big brother of TensorFlow
15 TFX: MLOps and deploying models with TensorFlow
Read more
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  1. ISBN-10
    1617298344
  2. ISBN-13
    978-1617298349
  3. Publisher
    Manning
  4. Publication date
    October 18, 2022
  5. Language
    English
  6. Dimensions
    7.38 x 1.6 x 9.25 inches
  7. Print length
    680 pages
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Editorial Reviews

Review

"A nice dive into TensorFlow 2. It outlines modern techniques and reinforces them with concrete sample projects."
— Joshua A. McAdams, Google

"Practical and hands-on. A valuable resource for practitioners and newbies."
— Amaresh Rajasekharan, IBM

"Comprehensive. Covers advanced topics such as atrous convolution, Transformers, and MLOps."
— Wei Luo, Deakin University

"Recommended for practitioners. There are code examples for every topic."
— Vidhya Vinay, Streamingo.ai

From the Back Cover

TensorFlow 2.0 in Action teaches you to use the new features of TensorFlow 2.0 to create advanced deep learning models. You'll learn by building hands-on projects, including an image classifier that can recognize objects, a French-to-English machine translator, and even a neural network that can write fiction. Thushan Ganegedara draws on his experience as a practitioner and teacher of deep learning to demystify concepts otherwise trapped in denseacademic papers. A top Stack Overflow contributor for deep learning and NLP, Thushan's quirky stories, real-world advice, and behind-the-scenes explanations make even complex ideas easy to understand! You'll dive into the details of modern deep learning techniques, including both transformer and attention models, and learn how pretrained models can solve your tricky data science problems. When you're done, you'll be ready to implement state-of-the-art deep learning applications and know the design secrets behind their success.

Product details

  • Publisher ‏ : ‎ Manning
  • Publication date ‏ : ‎ October 18, 2022
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 680 pages
  • ISBN-10 ‏ : ‎ 1617298344
  • ISBN-13 ‏ : ‎ 978-1617298349
  • Item Weight ‏ : ‎ 2.2 pounds
  • Dimensions ‏ : ‎ 7.38 x 1.6 x 9.25 inches
  • Best Sellers Rank: #2,872,270 in Books (See Top 100 in Books)
  • Customer Reviews:
    4.3 out of 5 stars (13)

About the author

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Thushan Ganegedara

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Customer reviews

4.3 out of 5 stars
13 global ratings
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Top reviews from the United States

  • Matteo
    5.0 out of 5 stars Exhaustive TensorFlow manual
    Reviewed in the United States on November 10, 2022
    Format: Paperback
    Good balance of theory and pragmatism.

    The author follows a structure I have seen in other books, introducing ML topics and TensorFlow syntax with simpler examples and Keras datasets, and going on to cover image classification with CNNs, NLP, and covering RNNs and other advanced topics.

    The examples have documentation mixed in with the code. Each section is broken down and explained in detail, going over code and theory, and everything is put together in the end.

    The examples in the book are great, and the author tries to prepare for examples beyond Keras datasets by synthetically corrupting some of the data or learning how to find the optimal attributes for a network.

    There's a lot of content and I'm still digesting the part on sequence-to-sequence learning. The book offers a wealth of knowledge on TensorFlow and the punctilious attention to the underlying principles carries the knowledge beyond the examples (it was easy for example to try out some of the concepts illustrated here in Tensorflow.js with different data).
    3 people found this helpful
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  • Carlos Roberto, GO4Electric
    5.0 out of 5 stars A must read book about Tensorflow 2.0
    Reviewed in the United States on December 15, 2022
    Format: Paperback
    In summary, this book is a comprehensive guide to TensorFlow 2, covering a wide range of topics from image processing to natural language processing. It is written in a way that is accessible to a variety of audiences, from graduate students to professional data scientists, and includes a series of exercises and answers to help readers solidify their understanding. The book compares and contrasts the different Keras APIs and focuses on sub-classing layers to improve model performance. It also provides useful tips for choosing CNN model parameters and explains how NLP models based on Transformers work. The book is well-illustrated and includes high-quality example code. It also covers advanced topics such as custom loss functions, model optimization, and MLOps using TensorFlow's TFX library. Overall, this book is a valuable resource for anyone interested in learning more about TensorFlow 2 and its applications.
    2 people found this helpful
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  • Tony Holdroyd
    5.0 out of 5 stars A thoughtful and well-written TensorFlow Tom.
    Reviewed in the United States on October 31, 2022
    Format: Paperback
    This is a very thoughtful, well-researched and well-written book. If you are in the market for an excellent tutorial reference to TensorFlow2 this book should be high on your list. The inclusion of TensorBoard, a crucial resource that every TensorFlow practitioner, at whatever level, needs to be fluent with the use of, is an excellent feature. . Deployment, treated skillfully here, is a topic often neglected in similar tomes.
    Just be aware that any book is going to be superceded by newer versions of TensorFlow by the time it is published although all the code here should run correctly on newer versions of TensorFlow than the version used in this book. TensorFlow isn't easy but the careful explanations and examples in this fine book should go a long way to making it as easy as possible (but no easier) for readers.
    3 people found this helpful
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  • Ganesh S
    5.0 out of 5 stars A fantastic Introduction to TensorFlow
    Reviewed in the United States on October 22, 2022
    Format: Paperback
    This is a fantastic and detailed introduction to Tensorflow.
    Part 1 covers foundations of TensorFlow and Keras.
    Part 2 covers the usual Image classifications, NL with Tensorflow, sentiment analysis, language modelling etc.
    Part 3 covers more advanced deep networks for complex problems including sequence to sequence learning, Transforms and TFX.

    The publisher for this book runs an "MEAP" early access program and I was fortunate to review the book in early form and I paid for this book myself. This is not a small book and there are over 600 pages of goodness to dive into.
    3 people found this helpful
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  • Kelvin D. Meeks
    5.0 out of 5 stars An exceptional and comprehensive book on TensorFlow 2.0
    Reviewed in the United States on October 28, 2022
    Format: Paperback
    An exceptional and comprehensive book on TensorFlow 2.0 - with a deep coverage and many practical hands-on exercises. A great balancing act between the practical vs. theoretical knowledge. An express route to developing foundational skills with TensorFlow 2.0
    3 people found this helpful
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