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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

Review questions and exercises

  1. What does cloud mean?
  2. What does cloud computing mean?
  3. Why do we care about sharing our working environments with others?
  4. How do we register on Anaconda Cloud?
  5. Do users need an account to use the Anaconda Cloud platform?
  6. How do we upload our notebook to Anaconda Cloud?
  7. Why is it important to share our projects?
  8. How do you share your project? Build a project and share it with someone else.
  9. How do you recreate your partner's Anaconda environment?
  10. What is the meaning of the following two command lines:
conda remove --name myenv -all 
conda info -envs 
  1. How can we launch a Jupyter QtConsole?
  2. Run a Jupyter notebook called Octave Maric.ipynb under the subdirectory of examples/Builtin Extension. Note that you have to find a way to install a package called octavemagic first.
  3. Share your environment with another person to see the effect.
  4. Generate a set...
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