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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

Two examples of using packages

It is always a good idea to use examples to illustrate how useful or important it is to understand some closely related packages. The first example is extremely simple: generate a QR code for the CNN website. It has just two lines. Note that you need to run install.packages("qrcode") if the package is not preinstalled:

> library(qrcode) 
> qrcode_gen("https://www.cnn.com") 

The generated QR code is shown here. Users can use the QR scanner installed on their cell phone to go to the CNN website:

For the second example, we believe the best example for the researchers and users in the area of data science is an R package called rattle. If a user hasn't preinstalled the package, they can type the following line of R code:

>install.packages("rattle")

To launch the package, type the following two lines of R code...

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