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MLX: Opinionated ML Pipelines in MLflow // Xiangrui Meng // Coffee Sessions #112

MLX: Opinionated ML Pipelines in MLflow // Xiangrui Meng // Coffee Sessions #112

FromMLOps.community


MLX: Opinionated ML Pipelines in MLflow // Xiangrui Meng // Coffee Sessions #112

FromMLOps.community

ratings:
Length:
50 minutes
Released:
Aug 3, 2022
Format:
Podcast episode

Description

MLOps Coffee Sessions #112 with Xiangrui Meng, Principal Software Engineer of Databricks, MLX: Opinionated ML Pipelines in MLflow co-hosted by Vishnu Rachakonda.

// Abstract
MLX 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.

// Bio
Xiangrui 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 board  
https://mlops.pallet.xyz/jobs

MLOps Swag/Merch
https://mlops-community.myshopify.com/

// Related Links
Good 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 ✌️ -------------
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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 to 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
Released:
Aug 3, 2022
Format:
Podcast episode

Titles in the series (100)

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.