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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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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

Summary

In this chapter, we have introduced some basic concepts, such as the reasons why we use Anaconda, and the advantages of using full-fledged Anaconda and/or its baby version, Miniconda. Then, it was shown that without installing Anaconda, we could still use it by visiting a designated website. We could also test a few simple programs there, writing in R, Python, Julia, or Octave.

In Chapter 2, Anaconda Installation, we will show you how to install Anaconda and test if the installation is successful. We will look at how to launch Jupyter, how to launch Python, Spyder, and R, and how to find related help. Most of those concepts or procedures are quite basic, so readers who are confident with those basic concepts can skip this chapter, Chapter 2, Anaconda Installation, and go to Chapter 3, Data Basics, directly.

You have been reading a chapter from
Hands-On Data Science with Anaconda
Published in: May 2018
Publisher: Packt
ISBN-13: 9781788831192
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