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Jupyter Cookbook

You're reading from   Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788839440
Length 238 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Toc

Table of Contents (12) Chapters Close

Preface 1. Installation and Setting up the Environment FREE CHAPTER 2. Adding an Engine 3. Accessing and Retrieving Data 4. Visualizing Your Analytics 5. Working with Widgets 6. Jupyter Dashboards 7. Sharing Your Code 8. Multiuser Jupyter 9. Interacting with Big Data 10. Jupyter Security 11. Jupyter Labs

Running your Notebook in AWS


Amazon Web Services (AWS) is a secure cloud platform that can be used to deploy web services. In our case, we want to install Jupyter on AWS and deploy our Notebook onto that service.

Getting ready

Signing up for AWS is easy enough at aws.amazon.com. Get ready though; the variety of services offered is amazing. For our implementation, we only need a smaller scale server (I selected micro) running Linux (I selected Ubuntu). Unless you are developing a Notebook that would draw a large audience to require a larger machine size, this should suffice.

How to do it...

For AWS, you have to use your own SSH shell; there is no browser SSH connection available (though I was able to do so on GC in a previous section).

There appears to be a delay in deploying on AWS. I am not sure why! There are no hardware changes involved, and all software and allocating another micro instance should be very quick.

Once your VM is running, connect via SSH to your instance. The connection information...

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