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Keras 2.x Projects

You're reading from   Keras 2.x Projects 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789536645
Length 394 pages
Edition 1st Edition
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Author (1):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Keras FREE CHAPTER 2. Modeling Real Estate Using Regression Analysis 3. Heart Disease Classification with Neural Networks 4. Concrete Quality Prediction Using Deep Neural Networks 5. Fashion Article Recognition Using Convolutional Neural Networks 6. Movie Reviews Sentiment Analysis Using Recurrent Neural Networks 7. Stock Volatility Forecasting Using Long Short-Term Memory 8. Reconstruction of Handwritten Digit Images Using Autoencoders 9. Robot Control System Using Deep Reinforcement Learning 10. Reuters Newswire Topics Classifier in Keras 11. What is Next? 12. Other Books You May Enjoy

Creating a linear regression model

A simple linear regression is easy to understand, but represents the basis of regression techniques. Once these concepts are understood, it will be easier for us to address the other types of regression. To begin with, let's take an example of applying linear regression that's been taken from the real world.

Consider some data that has been collected on a group of bikers, which consists of the following aspects:

  • Number of years of use
  • Number of kilometers traveled in one year
  • Number of falls

Through these techniques, we find that, on average, when the number of kilometers traveled increases, the number of falls also increases. By increasing the number of years of motorcycle usage and by increasing the experience, the number of falls tends to decrease.

The linear regression method consists of precisely identifying a line that is capable...

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