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TensorFlow 2.0 Quick Start Guide

You're reading from   TensorFlow 2.0 Quick Start Guide Get up to speed with the newly introduced features of TensorFlow 2.0

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789530759
Length 196 pages
Edition 1st Edition
Languages
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Author (1):
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Tony Holdroyd Tony Holdroyd
Author Profile Icon Tony Holdroyd
Tony Holdroyd
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Introduction to TensorFlow 2.00 Alpha
2. Introducing TensorFlow 2 FREE CHAPTER 3. Keras, a High-Level API for TensorFlow 2 4. ANN Technologies Using TensorFlow 2 5. Section 2: Supervised and Unsupervised Learning in TensorFlow 2.00 Alpha
6. Supervised Machine Learning Using TensorFlow 2 7. Unsupervised Learning Using TensorFlow 2 8. Section 3: Neural Network Applications of TensorFlow 2.00 Alpha
9. Recognizing Images with TensorFlow 2 10. Neural Style Transfer Using TensorFlow 2 11. Recurrent Neural Networks Using TensorFlow 2 12. TensorFlow Estimators and TensorFlow Hub 13. Converting from tf1.12 to tf2
14. Other Books You May Enjoy

Supervised learning

Supervised learning is the machine learning scenario in which one or more data points from a set of data points is/are associated with a label. The model then learns to predict the labels for unseen data points. For our purposes, each data point will normally be a tensor and will be associated with a label. Supervised learning problems abound in computer vision; for example, an algorithm is shown many pictures of ripe and unripe tomatoes, together with a categorical label indicating whether or not they are ripe, and when the training has concluded, the model is able to predict the status of tomatoes that weren't in its training set. This could have a very direct application in a physical sorting mechanism for tomatoes; or an algorithm that could learn to predict the gender and age of a new face after it has been shown many examples, together with their...

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