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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

Questions

  1. How are images represented in computers?

Images are represented in computers as a group of pixels, with each pixel having its own intensity (value between 0 and 255). Color images have three channels (red, green, and blue) while grayscale images have only one channel.

  1. What are the fundamental building blocks of a CNN?

All convolutional neural network consists of convolution layers, pooling layers, and fully connected layers.

  1. What is the role of the convolutional and pooling layers?

The convolutional and pooling layers are responsible for extracting spatial characteristics from the images. For example, when training a CNN to identify images of cats, one such spatial characteristic would be the pointy ears of cats.

  1. What is the role of the fully connected layers?

The fully connected layers are similar to the those in MLPs and feedforward neural networks. Their...

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