26 min listen
Live from TWIMLcon! The Great MLOps Debate: End-to-End ML Platforms vs Specialized Tools - #597
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Live from TWIMLcon! The Great MLOps Debate: End-to-End ML Platforms vs Specialized Tools - #597
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
ratings:
Length:
48 minutes
Released:
Oct 31, 2022
Format:
Podcast episode
Description
Over the last few years, it’s been established that your ML team needs at least some basic tooling in order to be effective, providing support for various aspects of the machine learning workflow, from data acquisition and management, to model development and optimization, to model deployment and monitoring.
But how do you get there? Many tools available off the shelf, both commercial and open source, can help.
At the extremes, these tools can fall into one of a couple of buckets. End-to-end platforms that try to provide support for many aspects of the ML lifecycle, and specialized tools that offer deep functionality in a particular domain or area.
At TWIMLcon: AI Platforms 2022, our panelists debated the merits of these approaches in The Great MLOps Debate: End-to-End ML Platforms vs Specialized Tools.
But how do you get there? Many tools available off the shelf, both commercial and open source, can help.
At the extremes, these tools can fall into one of a couple of buckets. End-to-end platforms that try to provide support for many aspects of the ML lifecycle, and specialized tools that offer deep functionality in a particular domain or area.
At TWIMLcon: AI Platforms 2022, our panelists debated the merits of these approaches in The Great MLOps Debate: End-to-End ML Platforms vs Specialized Tools.
Released:
Oct 31, 2022
Format:
Podcast episode
Titles in the series (100)
This Week in ML & AI - 6/24/16: Dueling Neural Networks at ICML, Plus Training a Robotic Housekeeper: This Week in Machine Learning & AI brings you the… by The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)