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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):

Alex Galea

Luis Capelo

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Table of Contents (9) Chapters

Preface

1. Jupyter Fundamentals

2. Data Cleaning and Advanced Machine Learning FREE CHAPTER

3. Web Scraping and Interactive Visualizations

4. Introduction to Neural Networks and Deep Learning

5. Model Architecture

6. Model Evaluation and Optimization

7. Productization

8. Other Books You May Enjoy

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Summary

In this chapter, we have assembled a complete deep learning system: from data to prediction. The model created in this activity needs a number of improvements before it can be considered useful. However, it serves as a great starting point from which we will continuously improve.

Our next chapter will explore techniques for measuring the performance of our model and will continue to make modifications until we reach a model that is both useful and robust.

The rest of the chapter is locked

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Authors (2)

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 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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