EPISODE · Aug 3, 2022 · 50 MIN
MLX: Opinionated ML Pipelines in MLflow // Xiangrui Meng // Coffee Sessions #112
from MLOps.community · host Demetrios
MLOps Coffee Sessions #112 with Xiangrui Meng, Principal Software Engineer of Databricks, MLX: Opinionated ML Pipelines in MLflow, co-hosted by Vishnu Rachakonda.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractMLX is to enable data scientists to stay mostly within their comfort zone, utilizing their expert knowledge while following the best practices in ML development and delivering production-ready ML projects, with little help from production engineers and DevOps.// BioXiangrui Meng is a Principal Software Engineer at Databricks and an Apache Spark PMC member. His main interests center around simplifying the end-to-end user experience of building machine learning applications, from algorithms to platforms and to operations.// MLOps Jobs boardjobs.mlops.community MLOps Swag/Merchhttps://mlops-community.myshopify.com/// Related LinksGood Strategy Bad Strategy: The Difference and Why It Matters, book by Richard Rumelt:https://www.amazon.com/Good-Strategy-Bad-Difference-Matters/dp/0307886239--------------- ✌️Connect With Us ✌️ -------------Join our Slack community: https://go.mlops.community/slackFollow us on Twitter: @mlopscommunitySign up for the next meetup: https://go.mlops.community/registerCatch all episodes, blogs, newsletters, and more: https://mlops.community/Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/Connect with Vishnu on LinkedIn: https://www.linkedin.com/in/vrachakonda/Connect with Xiangrui on LinkedIn: https://www.linkedin.com/in/mengxr/Timestamps:[00:00] Introduction to Xiangrui Meng[00:39] Takeaways[02:09] Xiangrui's background[03:38] What kept Xiangrui in Databricks[07:33] What needs to be done to get there[09:20] Machine Learning passion of Xiangrui[11:52] Changes in building that keep you fresh for the future[14:35] Evolution core challenges to real-time and use cases in real-time[17:33] DevOps + DataOps + ModelOps = MLOps[19:21] MLFlow Support[21:37] Notebooks to production debates [25:42] Companies tackling Notebooks for production[27:40] MLOoops stories[31:03] Opinionated MLOps productionizing in a good way[40:23] Xiangrui's MLOps Vision[44:47] Lightning round[48:45] Wrap up
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MLX: Opinionated ML Pipelines in MLflow // Xiangrui Meng // Coffee Sessions #112
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