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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

Importance of data visualization

For learners, users, or researchers in the areas of data science and business analytics, using various types of graphs, pie charts, bar charts, and other visual means to show some underlying trend or pattern implied by data is vital to understand data and to help researchers present their data to their audience or clients better. There are several reasons for this. First, it is sometimes difficult to describe our findings, especially when we have several patterns or influencing factors. With several separate graphs and a joint one, complex relationships can be understood or explained better.

We can use graphs or pictures to explain certain algorithms, such as the Bisection method (see the section related to dynamic visual presentation, Dynamic visualization).

We can also use relative sizes to represent different meanings. In finance, a basic concept...

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