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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 2. Predicting Diabetes with Multilayer Perceptrons FREE CHAPTER 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

Machine Learning and Neural Networks 101

Artificial intelligence (AI) has captured much of our attention in recent years. From face recognition security systems in our smartphones to booking an Uber ride through Alexa, AI has become ubiquitous in our everyday lives. Still, we are constantly being reminded that the full potential of AI has not yet been realized, and that AI will become an even bigger transformative factor in our lives.

When we look at the horizon, we can see the relentless progression of AI with its promise to better our everyday lives. Powered by AI, self-driving cars are becoming less science fiction, and more of a reality. Self-driving cars aim to reduce traffic accidents by eliminating human error, ultimately improving our lives. Similarly, the usage of AI in healthcare promises to improve outcomes. Notably, the UK's National Health Service has announced an ambitious AI project to diagnose early-stage cancer, which can potentially save thousands of lives.

The transformative nature of AI has led experts to call it the fourth industrial revolution. AI is the catalyst that will shape modern industries, and having knowledge of AI is essential in this new world. By the end of this book, you will have a better understanding of the algorithms that power AI, and will have developed real-life projects using these cutting-edge algorithms.

In this chapter, we will cover the following topics:

  • A primer on machine learning and neural networks
  • Setting up your computer for machine learning
  • Executing your machine learning projects from start to finish using the machine learning workflow
  • Creating your own neural network from scratch in Python without using a machine learning library
  • Using pandas for data analysis in Python
  • Leveraging machine learning libraries such as Keras to build powerful neural networks
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