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Hands-On Data Science with Anaconda

You're reading from  Hands-On Data Science with Anaconda

Product type Book
Published in May 2018
Publisher Packt
ISBN-13 9781788831192
Pages 364 pages
Edition 1st Edition
Languages
Authors (2):
Yuxing Yan Yuxing Yan
Profile icon Yuxing Yan
James Yan James Yan
Profile icon James Yan
View More author details

Table of Contents (15) Chapters

Preface 1. Ecosystem of Anaconda 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 first discussed the importance of managing packages. Then, we have shown how to find all the available packages for R, Python, Julia, and Octave, how to install and update individual packages, and how to find the manual for teaching the packages. In addition, we have explained the issue of package dependencies and how to make our programming a little easier when dealing with packages. The topic of systematic environment was touched on as well.

In Chapter 7, Optimization in Anaconda, we will discuss several topics around optimization, such as general issues for optimization problems and expressing various kinds of optimization problems (for example, LP and quadratic optimization). Several examples are offered to make our discussion more practice-oriented, such as how to choose an optimal stock portfolio and how to optimize wealth and resources to...

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