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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

Model architecture

Let's take a look at the model architecture of our IMDb movie review sentiment analyzer, shown in the following diagram:

This should be fairly familiar to you by now! Let's go through each component briefly.

Input

The input to our neural network shall be IMDb movie reviews. The reviews will be in the form of English sentences. As we've seen, the dataset provided in Keras has already encoded the English words into numbers, as neural networks require numerical inputs. However, there remains a problem we need to address. As we know, movie reviews have different lengths. If we were to represent the reviews as a vector, then different reviews would have different vector lengths, which is not...

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