You can use Jupyter Notebooks to share Python code and its output with third parties, to run code with live interactive feedback, or to systematically track and document the progress of your work.

The advantage of using Jupyter instead of an ordinary interactive interpreter like Python's is that Jupyter automatically saves a record of what you do.

Any Python module that runs well in a notebook interface (essentially, anything that writes to stdout as part of its behavior) is a good candidate for this. Sharing code and data generally.

Installing Python This step may sound redundant if youâ re already knee-deep into programming, but youâ ll need to install Python on your PC to use GPU-accelerated AI in Jupyter Notebook.

In this video from the Blue Waters Symposium, Roland Haas from NCSA presents: Tutorial: How to use Jupyter Notebooks. "Jupyter notebooks provide a web-based interface to Python, R, Julia and other ...

Course Objectives: Using Python in Jupyter Notebooks Gathering input and manipulating input/output Building reusable Functions with parameters and return values Decisions and repetition using ...

Because of the client/server architecture, it is very simple to share notebooks with other users. You can — in theory — use Jupyter for anything you could use Python for.

It’s common for us to work on these projects using Jupyter notebooks because they’re great, fast, simple, and they allow us to interact and play with our data.

Use this in-depth Jupyter Notebook vs. PyCharm comparison to learn more about their features and pricing and to find your best fit.