Karsten S. Nielsen PRO

karstenskyt

AI & ML interests

None yet

Recent Activity

updated a dataset about 1 hour ago

luxury-lakehouse/obso-pausa-inputs

updated a dataset about 1 hour ago

luxury-lakehouse/space-creation-values

updated a dataset about 1 hour ago

luxury-lakehouse/obso-pausa-values

View all activity

Organizations

Posts 4

Post

2290

🚀 𝗟𝗮𝘂𝗻𝗰𝗵𝗶𝗻𝗴 𝘁𝗵𝗲 𝗔𝗜/𝗠𝗟 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱

Now that our Taipy architecture is humming along on Hugging Face Spaces, we just shipped the most complex feature of the (𝘙𝘪𝘨𝘩𝘵! 𝘓𝘶𝘹𝘶𝘳𝘺!) 𝘓𝘢𝘬𝘦𝘩𝘰𝘶𝘴𝘦 to date: the 𝗔𝗜/𝗠𝗟 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱.

Managing 16 different machine learning pipelines (from Expected Goals to Space Creation) across Databricks Serverless and HF Jobs is a logistical challenge. To solve this, we built a dynamic operations center (the 13th page in our app).

It features:

  • 𝗔𝗻 𝗶𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝘃𝗲 𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝘆 𝗗𝗔𝗚: Powered by Cytoscape.js, it visually maps exactly how our models and data grids feed into each other.

  • 𝗥𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗺𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴: Tracks run volumes and data freshness SLAs across the entire platform.

  • 𝗔 𝟯-𝘁𝗶𝗲𝗿 𝗵𝘆𝗯𝗿𝗶𝗱 𝗰𝗼𝘀𝘁 𝗲𝗻𝗴𝗶𝗻𝗲: Merges "cold" Databricks billing data with "warm/hot" live HF Jobs estimates to give a unified view of pipeline expenses.

Check out the live interactive graph here:
luxury-lakehouse/soccer-analytics-app

Post

156

🚀 𝗟𝘂𝘅𝘂𝗿𝘆 𝗟𝗮𝗸𝗲𝗵𝗼𝘂𝘀𝗲 𝗨𝗜 𝗨𝗽𝗴𝗿𝗮𝗱𝗲: 𝗠𝗶𝗴𝗿𝗮𝘁𝗶𝗻𝗴 𝘁𝗼 𝗧𝗮𝗶𝗽𝘆

I’m excited to share a major frontend architecture upgrade for the (𝘙𝘪𝘨𝘩𝘵! 𝘓𝘶𝘹𝘶𝘳𝘺!) 𝘓𝘢𝘬𝘦𝘩𝘰𝘶𝘴𝘦 open-source soccer analytics platform. We have officially migrated the dashboard UI from 𝗦𝘁𝗿𝗲𝗮𝗺𝗹𝗶𝘁 to 𝗧𝗮𝗶𝗽𝘆, and it is now live on Hugging Face Spaces.

𝗪𝗵𝘆 𝘁𝗵𝗲 𝘀𝘄𝗶𝘁𝗰𝗵?

While Streamlit was fantastic for prototyping our initial 12 dashboards, we started running into some persistent "jittery" rendering issues as the app grew more complex—specifically when handling 𝟯𝟴𝗠+ 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝗳𝗿𝗮𝗺𝗲𝘀 across 5 professional data providers.

Rebuilding the app in Taipy (running via the Docker SDK on HF Spaces) immediately smoothed out those state-management hiccups. The difference is exceptionally noticeable when interacting with our native Plotly charts, like the Pass Networks and Pitch Control surfaces.

More importantly, this architectural switch sets the foundation for our next major roadmap milestone. Taipy natively excels at managing 𝗮𝘀𝘆𝗻𝗰𝗵𝗿𝗼𝗻𝗼𝘂𝘀 𝗯𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱 𝘁𝗮𝘀𝗸𝘀 and 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴—capabilities we will be heavily leaning into as we start rolling out some advanced, long-running ML training pipelines soon. 👀

Check out the smoother, faster V2 of the platform here:
luxury-lakehouse/soccer-analytics-app