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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 2. Anaconda Installation FREE CHAPTER 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

UCI machine learning

The UCI maintains 413 datasets, as of 1/10/2018, for machine learning: http://archive.ics.uci.edu/ml/index.php. The following screenshot shows the top three downloaded datasets:

For the number one downloaded dataset called Iris, we have the following information:

The beauty of these datasets is that they give quite detailed information such as the source, the creator or donator, a description, and even citations.

The following table shows several potential public data sources for users in the area of data science and business analytics:

Name
Web page
Data types

UCI


http://archive.ics.uci.edu/ml/index.php

Data for machine learning

World Health Organization


http://www.who.int/en/

Healthcare data

Amazon Web Services

https://aws.amazon.com/cn/datasets/?nc1=h_ls

Web usage

Data.gov (US Government Open Data)

https://www.data...

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