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Jupyter for Data Science

You're reading from Jupyter for Data Science

Product type Book

Published in Oct 2017

Publisher Packt

ISBN-13 9781785880070

Pages 242 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Dan Toomey

Table of Contents (17) Chapters

Title Page

Credits

About the Author

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Jupyter and Data Science

2. Working with Analytical Data on Jupyter

3. Data Visualization and Prediction

4. Data Mining and SQL Queries

5. R with Jupyter

6. Data Wrangling

7. Jupyter Dashboards

8. Statistical Modeling

9. Machine Learning Using Jupyter

10. Optimizing Jupyter Notebooks

Sharing Jupyter Notebooks

Jupyter Notebooks can be shared by placing the notebook on a server (there are several kinds) or converting the notebook to another format (it will not be interactive, but the content will be available).

Sharing Jupyter Notebook on a notebook server

Built into the notebook configuration are extensions that can be used to expose a notebook server, directly. The notebook configuration can be generated using the following command:

Jupyter Notebook -generate-config

In the resulting jupyter_notebook_config.py file there are settings that can be used to set:

IP/port address of your notebook
Encryption certificate location
Password

By setting this and starting Jupyter you should be able to access the notebook at the IP address specified from other machines in your network.

Note

You should work with your network security personnel before doing so.

Sharing encrypted Jupyter Notebook on a notebook server

If you specify the certificate information correctly in the previous configuration...

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Authors (1)

Dan Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.

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