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Keras 2.x Projects

You're reading from Keras 2.x Projects

Product type Book

Published in Dec 2018

Publisher Packt

ISBN-13 9781789536645

Pages 394 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Giuseppe Ciaburro

Table of Contents (13) Chapters

Preface

1. Getting Started with Keras

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

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Pattern recognition using a Keras neural network

Heart diseases are often underestimated, but, in reality, they are the leading cause of death in the world. Among them, coronary artery disease (CAD) accounts for about a third of all deaths worldwide in people over 35 years of age. CAD is the result of arteriosclerosis, which consists in the narrowing of the blood vessels and the hardening of its walls. In some cases, CAD can completely block the influx of oxygen-rich blood to the heart muscle, causing a heart attack.

CAD is caused by an accumulation of waxy grease deposits on the inner walls of the arteries. These deposits consist of cholesterol, calcium, and other substances that travel in the blood; the product of their accumulation is called atherosclerotic plaque. This plaque can clog the coronary arteries and make them rigid and irregular, causing the so-called hardening...

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Authors (1)

Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).

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