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Applied Deep Learning with Python

You're reading from Applied Deep Learning with Python Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions

Product type Paperback

Published in Aug 2018

Publisher

ISBN-13 9781789804744

Length 334 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Authors (2):

Galea

Luis Capelo

View More author details

Table of Contents (14) Chapters

Title Page

Copyright and Credits

Packt Upsell

Contributors

Preface

1. Jupyter Fundamentals FREE CHAPTER

2. Data Cleaning and Advanced Machine Learning

3. Web Scraping and Interactive Visualizations

4. Introduction to Neural Networks and Deep Learning

5. Model Architecture

6. Model Evaluation and Optimization

7. Productization

1. Other Books You May Enjoy

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Index

What are Neural Networks?

Neural networks—also known as Artificial Neural Networks—were fist proposed in the 40s by MIT professors Warren McCullough and Walter Pitts.

Note

For more information refer, Explained: Neural networks. MIT News Office,April 14, 2017. Available at:http://news.mit.edu/2017/explained-neural-networksdeep-learning-0414.

Inspired by advancements in neuroscience, they proposed to create a computer system that reproduced how the brain works (human or otherwise). At its core was the idea of a computer system that worked as an interconnected network. That is, a system that has many simple components. These components both interpret data and influence each other on how to interpret data. This same core idea remains today.

Deep learning is largely considered the contemporary study of neural networks. Think of it as a current name given to neural networks. The main difference is that the neural networks used in deep learning are typically far greater in size—that is, they have many...

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Authors (2)

Galea

Galea

Alex Galea has been professionally practicing data analytics since graduating with a masters degree in physics from the University of Guelph, Canada. He developed a keen interest in Python while researching quantum gases as part of his graduate studies. Alex is currently doing web data analytics, where Python continues to play a key role in his work. He is a frequent blogger about data-centric projects that involve Python and Jupyter Notebooks.

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Luis Capelo

Luis Capelo

Luis Capelo is a Harvard-trained analyst and a programmer, who specializes in designing and developing data science products. He is based in New York City, America. Luis is the head of the Data Products team at Forbes, where they investigate new techniques for optimizing article performance and create clever bots that help them distribute their content. He worked for the United Nations as part of the Humanitarian Data Exchange team (founders of the Center for Humanitarian Data). Later on, he led a team of scientists at the Flowminder Foundation, developing models for assisting the humanitarian community. Luis is a native of Havana, Cuba, and the founder and owner of a small consultancy firm dedicated to supporting the nascent Cuban private sector.

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