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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

Predicting Diabetes with Multilayer Perceptrons

In the first chapter, we went through the inner workings of a neural network, how to build our own neural network using Python libraries such as Keras, as well as the end-to-end machine learning workflow. In this chapter, we will apply what we have learned to build a multilayer perceptron (MLP) that can predict whether a patient is at risk of diabetes. This marks the first neural network project that we will build from scratch.

In this chapter, we will cover the following topics:

  • Understanding the problem that we're trying to tackle—diabetes mellitus
  • How AI is being used in healthcare today, and how AI will continue to transform healthcare
  • An in-depth analysis of the diabetes mellitus dataset, including data visualization using Python
  • Understanding MLPs, and the model architecture that we will use
  • A step-by-step guide...
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