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The Deep Learning Workshop

You're reading from   The Deep Learning Workshop Learn the skills you need to develop your own next-generation deep learning models with TensorFlow and Keras

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839219856
Length 474 pages
Edition 1st Edition
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Authors (5):
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Nipun Sadvilkar Nipun Sadvilkar
Author Profile Icon Nipun Sadvilkar
Nipun Sadvilkar
Thomas Joseph Thomas Joseph
Author Profile Icon Thomas Joseph
Thomas Joseph
Anthony So Anthony So
Author Profile Icon Anthony So
Anthony So
Mohan Kumar Silaparasetty Mohan Kumar Silaparasetty
Author Profile Icon Mohan Kumar Silaparasetty
Mohan Kumar Silaparasetty
Mirza Rahim Baig Mirza Rahim Baig
Author Profile Icon Mirza Rahim Baig
Mirza Rahim Baig
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Toc

Table of Contents (9) Chapters Close

Preface
1. Building Blocks of Deep Learning 2. Neural Networks FREE CHAPTER 3. Image Classification with Convolutional Neural Networks (CNNs) 4. Deep Learning for Text – Embeddings 5. Deep Learning for Sequences 6. LSTMs, GRUs, and Advanced RNNs 7. Generative Adversarial Networks Appendix

Image Processing

Now that we know how a digital image is represented, let's discuss how computers can use this information to find patterns that will be used to classify an image or localize objects. So, in order to get any useful or actionable information from an image, a computer has to resolve an image into a recognizable or known pattern. As for any machine learning algorithm, computer vision needs some features in order to learn patterns.

Unlike structured data, where each feature is well defined in advance and stored in separate columns, images don't follow any specific pattern. It is impossible to say, for instance, that the third line will always contain the eye of an animal or that the bottom left corner will always represent a red, round-shaped object. Images can be of anything and don't follow any structure. This is why they are considered to be unstructured data.

However, images do contain features. They contain different shapes (lines, circles, rectangles...

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