Overview
- Study diagrams, tables, flowcharts, and other such visual aids to interact visually with deep learning information
- Troubleshoot deep learning projects
- Work through deep learning projects line-by-line to understand the concepts and build no them
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About this book
Deep learning is quickly integrating itself into the technology landscape. Its applications range from applicable data science to deep fakes and so much more. It is crucial for aspiring data scientists or those who want to enter the field of AI to understand deep learning concepts.
The best way to learn is by doing. You'll develop a working knowledge of not only TensorFlow, but also related technologies such as Python and Keras. You'll also work with Neural Networks and other deep learning concepts. By the end of the book, you'll have a collection of unique projects that you can add to your GitHub profiles and expand on for professional application.
What You'll Learn
- Grasp the basic process of neural networks through projects, such as creating music
- Restore and colorize black and white images with deep learning processes
Who This Book Is For
Beginners new to TensorFlow and Python.
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Keywords
Table of contents (9 chapters)
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Deep Learning Projects Using TensorFlow 2
Book Subtitle: Neural Network Development with Python and Keras
Authors: Vinita Silaparasetty
DOI: https://doi.org/10.1007/978-1-4842-5802-6
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Vinita Silaparasetty 2020
Softcover ISBN: 978-1-4842-5801-9Published: 25 July 2020
eBook ISBN: 978-1-4842-5802-6Published: 24 July 2020
Edition Number: 1
Number of Pages: XXV, 421
Number of Illustrations: 147 b/w illustrations
Topics: Artificial Intelligence