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Deep Learning for Computer Vision

You're reading from   Deep Learning for Computer Vision Expert techniques to train advanced neural networks using TensorFlow and Keras

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788295628
Length 310 pages
Edition 1st Edition
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Author (1):
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Rajalingappaa Shanmugamani Rajalingappaa Shanmugamani
Author Profile Icon Rajalingappaa Shanmugamani
Rajalingappaa Shanmugamani
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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Image Classification 3. Image Retrieval 4. Object Detection 5. Semantic Segmentation 6. Similarity Learning 7. Image Captioning 8. Generative Models 9. Video Classification 10. Deployment 11. Other Books You May Enjoy

Training the MNIST model in Keras

In this section, we will use the same model as defined in the previous section using tf.keras APIs. It is better to learn both Keras and layers packages from TensorFlow as they could be seen at several open source codes. The objective of the book is to make you understand various offerings of TensorFlow so that you can build products on top of it. 

"Code is read more often than it is written."

Bearing in mind the preceding quote, you are shown how to implement the same model using various APIs. Open source code of any implementation of the latest algorithms will be a mix of these APIs. Next, we will start with the Keras implementation. 

Preparing the dataset

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