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Posted 5 Mar 2019
Licenced CPOL

Analyzing Twitch Channel Viewership with Python and Intel

, 5 Mar 2019
Jeff pulls together what he's learned about Python and Jupyter notebooks to do some analysis on the viewership of his Twitch channel. What factors can he alter to increase viewership?

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Using Docker, Jupyter Notebooks, and the Intel Distribution for Python Jeff looks at the past performance of his Twitch stream to look at the number of users chatting, or number of chat messages there are to determine how long people stay viewing. Does that impact the maximum number of viewers, or average number, if they get talking about something that's interesting?

Jeff uses a Python model with linear regression with the Intel Python distribution to make a prediction based on his data to see if he can get more viewership on his Twitch channel.

License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

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About the Author

Jeffrey T. Fritz
Program Manager
United States United States
Jeff Fritz is a senior program manager in Microsoft’s Developer Division working on the .NET Community Team. As a long time web developer and application architect with experience in large and small applications across a variety of verticals, he knows how to build for performance and practicality. Four days a week, you can catch Jeff hosting a live video stream called 'Fritz and Friends' at twitch.tv/csharpfritz. You can also learn from Jeff on WintellectNow and Pluralsight, follow him on twitter @csharpfritz, and read his blog at jeffreyfritz.com

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