https://peertube.watch/videos/watch/667ed1e2-39d5-425c-af6d-7eb29bf7a643 Jupyter notebooks play a crucial role in the development stage for data analytics, machine learning, and other data-driven applications. However, moving them into a production environment often leads to a complex set of challenges.  Challenges related to production readiness, version control, testing, reproducibility, and modularity are common.     In this talk, we will delve into the specifics of these challenges and demonstrate how our tool, Versatile Data Kit (VDK), effectively addresses them. From deploying production-relevant code to ensuring linear execution for reproducibility, we will provide insights into practical solutions that could enhance efficiency in your data analytics and machine learning workflows. This session is aimed at those looking to understand the complexities of productionizing notebooks and explore potential methods to overcome these challenges. Benefits to the Ecosystem - solutions to several specific pain points of Productionizing Jupyter notebooks. For this talk, some prior knowledge of Jupyter Notebooks is necessary. Speakers: Antoni Ivanov, Antoni Ivanov, Track: HPC, Big Data & Data Science devroom, Room: UA2.118 (Henriot), When: Saturday 3 February 2024, 11:00–11:30 (Brussels time), Schedule: FOSDEM 2024 event page, Slides & links Presentation slides, Licence: Creative Commons Attribution 2.0 Belgium (CC BY 2.0 BE) (as stated in the FOSDEM video archive). Attribution: “Productionizing Jupyter Notebooks” by Antoni Ivanov, Antoni Ivanov, FOSDEM 2024. Original recording: 2024/ua2118/fosdem-2024-1740-productionizing-jupyter-notebooks.av1.webm from the FOSDEM video archive. This channel is an unofficial mirror; FOSDEM is a free and non-commercial event organised by the community for the community. Wed, 14 Oct 2026 05:02:56 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://peertube.watch https://peertube.watch/lazy-static/avatars/3b284627-b75f-409e-ac2e-10f4c2946f43.png https://peertube.watch/videos/watch/667ed1e2-39d5-425c-af6d-7eb29bf7a643 All rights reserved, unless otherwise specified in the terms specified at https://peertube.watch/about and potential licenses granted by each content's rightholder.