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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

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Product type Paperback
Published in Aug 2018
Publisher
ISBN-13 9781789804744
Length 334 pages
Edition 1st Edition
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Authors (2):
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Alex Galea Alex Galea
Author Profile Icon Alex Galea
Alex Galea
Luis Capelo Luis Capelo
Author Profile Icon Luis Capelo
Luis Capelo
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Deploying a Model as a Web Application

In this section, we will deploy our model as a web application. We will use an example web application—called "cryptonic"—to deploy our model, exploring its architecture so that we can make modifications in the future. The intention is to have you use this application as a starter for more complex applications; a starter that is fully working and can be expanded as you see fit.

Aside from familiarity with Python, this topic assumes familiarity with creating web applications. Specifically, we assume that you have some knowledge about web servers, routing, the HTTP protocol, and caching. You will be able to locally deploy the demonstrated cryptonic application without extensive knowledge of these topics, but learning these topics will make any future development much easier.

Finally, Docker is used to deploy our web...

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