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Hands-On Data Science with Anaconda

You're reading from   Hands-On Data Science with Anaconda Utilize the right mix of tools to create high-performance data science applications

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788831192
Length 364 pages
Edition 1st Edition
Languages
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Authors (2):
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James Yan James Yan
Author Profile Icon James Yan
James Yan
Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Toc

Table of Contents (15) Chapters Close

Preface 1. Ecosystem of Anaconda FREE CHAPTER 2. Anaconda Installation 3. Data Basics 4. Data Visualization 5. Statistical Modeling in Anaconda 6. Managing Packages 7. Optimization in Anaconda 8. Unsupervised Learning in Anaconda 9. Supervised Learning in Anaconda 10. Predictive Data Analytics – Modeling and Validation 11. Anaconda Cloud 12. Distributed Computing, Parallel Computing, and HPCC 13. References 14. Other Books You May Enjoy

Anaconda add-on

The following information is from the Anaconda Addon Development Guide.

An Anaconda add-on is a Python package containing a directory with an __init__.py file and other source directories (sub packages) inside. Because Python allows importing each package name only once, the package top-level directory name must be unique. At the same time, the name can be arbitrary, because add-ons are loaded regardless of their name; the only requirement is that they must be placed in a specific directory.

The suggested naming convention for add-ons is therefore similar to that of Java packages or D-Bus service names: prefix the add-on name with the reversed domain name of your organization, using underscores (_) instead of dots so that the directory name is a valid identifier for a Python package. An example add-on name following these suggestions would therefore be, for example...

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