2024年5月22日 #mlopsコミュニティ
同年度のMLOps研修資料はこちらです。 (1/4) CyberAgent AI事業本部2024年度MLOps研修Container編: https://speakerdeck.com/szma5a/container-for-mlops (2/4) CyberAgent AI事業本部2024年度MLOps研修基礎編: https://speakerdeck.com/nsakki55/mlops-basic (3/4) CyberAgent AI事業本部2024年度MLOps研修応用編: https://speakerdeck.com/tyaba/mlops-handson (4/4) CyberAgent AI事業本部2024年度MLOps研修実践編: https://speakerdeck.com/hosimesi11/mlops-practice
BlogHow To Organize Continuous Delivery of ML/AI Systems: a 10-Stage Maturity Model This article outlines ten stages of operational maturity for deploying ML/AI systems to production. Which stage are you at? Every production-oriented ML/AI team grapples with the same challenge: how to work with data, code, and models effectively so that projects are readily deployable to production. The challenge
AWS Machine Learning Blog How LotteON built a personalized recommendation system using Amazon SageMaker and MLOps This post is co-written with HyeKyung Yang, Jieun Lim, and SeungBum Shim from LotteON. LotteON aims to be a platform that not only sells products, but also provides a personalized recommendation experience tailored to your preferred lifestyle. LotteON operates various specialty stores,
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く