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|a Q325.5
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| 100 |
1 |
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|a Hua, Quan,
|e author.
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| 245 |
1 |
0 |
|a Machine learning with TensorFlow 1.x :
|b second generation machine learning with Google's brainchild - TensorFlow 1.x /
|c Quan Hua, Shams Ul Azeem, Saif Ahmed.
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| 264 |
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1 |
|a Birmingham, UK :
|b Packt Publishing,
|c 2017.
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| 300 |
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|a 1 online resource (1 volume) :
|b illustrations
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|a Online resource; title from title page (Safari, viewed January 3, 2018).
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| 505 |
0 |
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|a Machine learning with TensorFlow 1.x: second generation machine learning with Google's brainchild -- TensorFlow 1.x -- Credits -- About the Authors -- About the Reviewer -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- 1. Getting Started with TensorFlow -- 2. Your First Classifier -- 3. The TensorFlow Toolbox -- 4. Cats and Dogs -- 5. Sequence to Sequence Models-Parlez-vous Français? -- 6. Finding Meaning -- 7. Making Money with Machine Learning -- 8. The Doctor Will See You Now -- 9. Cruise Control -- Automation -- 10. Go Live and Go Big -- 11. Going Further -- 21 Problems -- 12. Advanced Installation -- Index.
|
| 520 |
3 |
|
|a Google's TensorFlow is a game changer in the world of machine learning. It has made machine learning faster, simpler, and more accessible than ever before. This book will teach you how to easily get started with machine learning using the power of Python and TensorFlow 1.x. Firstly, you'll cover the basic installation procedure and explore the capabilities of TensorFlow 1.x. This is followed by training and running the first classifier, and coverage of the unique features of the library including data flow graphs, training, and the visualization of performance with TensorBoard-all within an example-rich context using problems from multiple industries. You'll be able to further explore text and image analysis, and be introduced to CNN models and their setup in TensorFlow 1.x. Next, you'll implement a complete real-life production system from training to serving a deep learning model. As you advance you'll learn about Amazon Web Services (AWS) and create a deep neural network to solve a video action recognition problem. Lastly, you'll convert the Caffe model to TensorFlow and be introduced to the high-level TensorFlow library, TensorFlow-Slim. By the end of this book, you will be geared up to take on any challenges of implementing TensorFlow 1.x in your machine learning environment.
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| 650 |
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|a Machine learning.
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|a Artificial intelligence.
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| 650 |
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| 700 |
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|a Azeem, Shams Ul,
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| 700 |
1 |
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|a Ahmed, Saif,
|e author.
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|z Full Text (via O'Reilly/Safari)
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