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Neural Network Projects with Python

You're reading from Neural Network Projects with Python

Product type Book

Published in Feb 2019

Publisher Packt

ISBN-13 9781789138900

Pages 308 pages

Edition 1st Edition

Languages

Concepts

Neural Networks

Author (1):

James Loy

Table of Contents (10) Chapters

Preface

Machine Learning and Neural Networks 101

Predicting Diabetes with Multilayer Perceptrons

Predicting Taxi Fares with Deep Feedforward Networks

Cats Versus Dogs - Image Classification Using CNNs

Removing Noise from Images Using Autoencoders

Sentiment Analysis of Movie Reviews Using LSTM

Implementing a Facial Recognition System with Neural Networks

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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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Authors (1)

James Loy

James Loy has more than five years, expert experience in data science in the finance and healthcare industries. He has worked with the largest bank in Singapore to drive innovation and improve customer loyalty through predictive analytics. He has also experience in the healthcare sector, where he applied data analytics to improve decision-making in hospitals. He has a master's degree in computer science from Georgia Tech, with a specialization in machine learning. His research interest includes deep learning and applied machine learning, as well as developing computer-vision-based AI agents for automation in industry. He writes on Towards Data Science, a popular machine learning website with more than 3 million views per month.

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