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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

The faces dataset

Let's now look at the faces dataset that we will be using for this project. There are numerous publicly available faces dataset for use, as consolidated at http://www.face-rec.org/databases/.

While there are many face datasets that we can use, the most appropriate dataset for training a facial recognition system should contain photos of different subjects, with each subject having multiple photos taken from different angles. It should also ideally contain photos of the subject wearing different expressions (eyes closed and so on), as such photos are commonly encountered by facial recognition systems.

With these considerations in mind, the dataset that we have chosen is the Database of Faces, created by AT&T Laboratories, Cambridge. The database contains photos of 40 subjects, with 10 photos of each subject. The photos of each subject were taken under...

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