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Mastering Predictive Analytics with Python

You're reading from   Mastering Predictive Analytics with Python Exploit the power of data in your business by building advanced predictive modeling applications with Python

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Product type Paperback
Published in Aug 2016
Publisher
ISBN-13 9781785882715
Length 334 pages
Edition 1st Edition
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Author (1):
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Joseph Babcock Joseph Babcock
Author Profile Icon Joseph Babcock
Joseph Babcock
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Table of Contents (11) Chapters Close

Preface 1. From Data to Decisions – Getting Started with Analytic Applications FREE CHAPTER 2. Exploratory Data Analysis and Visualization in Python 3. Finding Patterns in the Noise – Clustering and Unsupervised Learning 4. Connecting the Dots with Models – Regression Methods 5. Putting Data in its Place – Classification Methods and Analysis 6. Words and Pixels – Working with Unstructured Data 7. Learning from the Bottom Up – Deep Networks and Unsupervised Features 8. Sharing Models with Prediction Services 9. Reporting and Testing – Iterating on Analytic Systems Index

The architecture of a prediction service


Now with a clear goal in mind—to share and scale the results of our predictive modeling using a web application—what are the components required to accomplish this objective?

The first is the client: this could be either a web browser or simply a user entering a curl command in the terminal (see Aside). In either case, the client sends requests using hypertext transfer protocol (HTTP), a standard transport convention to retrieve or transmit information over a network (Berners-Lee, Tim, Roy Fielding, and Henrik Frystyk. Hypertext transfer protocol--HTTP/1.0. No. RFC 1945. 1996). An important feature of the HTTP standard is that the client and server do not have to 'know' anything about how the other is implemented (for example, which programming language is used to write these components) because the message will remain consistent between them regardless by virtue of following the HTTP standard.

The next component is the server, which receives HTTP...

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