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Neural Network Projects with Python

You're reading from   Neural Network Projects with Python The ultimate guide to using Python to explore the true power of neural networks through six projects

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789138900
Length 308 pages
Edition 1st Edition
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Author (1):
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James Loy James Loy
Author Profile Icon James Loy
James Loy
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Table of Contents (10) Chapters Close

Preface 1. Machine Learning and Neural Networks 101 FREE CHAPTER 2. Predicting Diabetes with Multilayer Perceptrons 3. Predicting Taxi Fares with Deep Feedforward Networks 4. Cats Versus Dogs - Image Classification Using CNNs 5. Removing Noise from Images Using Autoencoders 6. Sentiment Analysis of Movie Reviews Using LSTM 7. Implementing a Facial Recognition System with Neural Networks 8. What's Next? 9. Other Books You May Enjoy

Building blocks of CNNs

One of the challenges faced in image classification is that the appearance of objects is dynamic. Just as there are many different breeds of cats and dogs, there are an infinite number of ways cats and dogs can appear in images. This makes it difficult for rudimentary image classification techniques, as it is impossible to show an infinite number of photos of cats and dogs to a computer.

However, this really shouldn't be a problem at all. Humans don't require an infinite number of photos of cats and dogs to differentiate between the two. A toddler can easily differentiate cats and dogs once he has seen just a few of them. If we think about how humans approach image classification, we notice that humans tend to look for landmark features while trying to identify an object. For example, we know that cats tend to be smaller in size compared to dogs...

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