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Python Data Mining Quick Start Guide

You're reading from   Python Data Mining Quick Start Guide A beginner's guide to extracting valuable insights from your data

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789800265
Length 188 pages
Edition 1st Edition
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Author (1):
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Nathan Greeneltch Nathan Greeneltch
Author Profile Icon Nathan Greeneltch
Nathan Greeneltch
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Table of Contents (9) Chapters Close

Preface 1. Data Mining and Getting Started with Python Tools FREE CHAPTER 2. Basic Terminology and Our End-to-End Example 3. Collecting, Exploring, and Visualizing Data 4. Cleaning and Readying Data for Analysis 5. Grouping and Clustering Data 6. Prediction with Regression and Classification 7. Advanced Topics - Building a Data Processing Pipeline and Deploying It 8. Other Books You May Enjoy

Advanced Topics - Building a Data Processing Pipeline and Deploying It

This chapter will cover the strategy of building a data analysis pipeline and deploying it to run in production on future, incoming data. It will also cover persistent model storage, which is required to distribute for deployment. This chapter will then cover the specific consequences that Python's interpreted nature has on deployment.

The following topics will be covered in this chapter:

  • Pipelining your analysis
  • Storing a model for deployment
  • Loading a deployed model
  • Python-specific deployment concerns
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