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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

Sequential problems in machine learning

Sequential problems are a class of problem in machine learning in which the order of the features presented to the model is important for making predictions. Sequential problems are commonly encountered in the following scenarios:

  • NLP, including sentiment analysis, language translation, and text prediction
  • Time series predictions

For example, let's consider the text prediction problem, as shown in the following screenshot, which falls under NLP:

Human beings have an innate ability for this, and it is trivial for us to know that the word in the blank is probably the word Japanese. The reason for this is that as we read the sentence, we process the words as a sequence. The sequence of the words captures the information required to make the prediction. By contrast, if we discard the sequential information and only consider the words...

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