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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

Dynamic visualization

Dynamic visualization means that we can see the concept or theory vividly, just like a video or movie. For example, in the Monte Carlo simulation, we could generate a set of random numbers from certain distributions, such as a uniform or a normal distribution. If we could show how particles moved within a range, learners would understand the concept of randomness better. This is like dropping red ink into a basin of water and observing how the ink diffuses. Another example is related to the so-called bisection method or bisection search. Assume that we have a database that contains daily trading data for over 5,000 stocks. There are many ways to retrieve one specific stock's information. One is called sequential search. In a sequential search, we pick up the first stock and compare it with our target. If it doesn't match, we go to the next stock...

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