On this episode of the AI Show, we're talking about MLOps. Seth welcomes Microsoft Data Scientist, Spyros Marketos, ML Engineer, Davide Fornelli and Data Engineer, Samarendra Panda. Together they make up an AI Taskforce and they'll give us a high-level intro into MLOps and share some of the surprises and lessons they've learned along the way! Jump to:[00:17] AI Show Intro[00:34] Welcome and Introductions[01:41] Use cases from the AI Taskforce[02:47] Commonalities across projects[03:50] Common challenges - from the Data Engineer perspective[06:47] Common challenges - from the ML Engineer perspective[08:46] Common challenges from the Data Science perspective[10:48] What does success in MLOps look like?[12:30] Surprising challenges working with customers and how to avoid them[19:27] Review - what is ML Ops[19:45] MLOps in Delivery mission[21:57] MLOps principles[27:52] Tips from the pros Learn more:Machine Learning for Data Scientists https://aka.ms/AIShow/MLforDataScientistsPakt: Principles of Data Science https://aka.ms/AIShow/DataSciencePacktZero to Hero Machine Learning on Azure https://aka.ms/ZerotoHero/MLonAzureZero to Hero Azure AI https://aka.ms/ZerotoHero/AzureAICreate a Free account (Azure) https://aka.ms/aishow-seth-azurefree Follow Seth https://twitter.com/sethjuarezFollow Spyros https://www.linkedin.com/in/smarketos/Follow Davide https://www.linkedin.com/in/davidefornelli/Follow Sam https://www.linkedin.com/in/samarendra-panda/ Don't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeAI Show Playlist https://aka.ms/AIShowPlaylist Join us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive