In this episode, we take a look at options for executing ML workloads on AWS. We will review what is available within the Amazon SageMaker toolset and what you can do outside of it.
- AWS re:View Ep17: ML Automation (MLOps) on AWS ( Download)
- AWS re:Invent 2022 - Better decisions with no-code ML using SageMaker Canvas, feat. Samsung (AIM207) ( Download)
- MLOps World Conference: From 12 Months to 30 Days to AI Deployment - An MLOps Journey ( Download)
- MLOps London July - Talks on AI Regulation and Production-Grade Pipelines ( Download)
- Machine Learning Maturity Model ( Download)
- Fireside Chat: Savin Goyal (ML Infra team (Metaflow), Netflix) with Matt Turck (Partner, FirstMark) ( Download)
- Comment mettre en place de saines pratiques en MLOps ( Download)
- India ML state of Nation By Saira Shaik Senior Technical Consultant (APAC) at AWS [MLDS2020] ( Download)
- Using TensorFlow on Google Cloud Platform | Karl Weinmeister ( Download)
- Vivek Kumar Managing Director at Springboard India | MLDS2020 ( Download)
- Deep Learning With PyTorch - Luca, Eli & Thomas | Podcast #38 ( Download)
- Stanford MLSys Seminar Episode 2: Matei Zaharia ( Download)
- ML Systems in Production - Designing ML Systems Reading Group ( Download)
- Retail & Consumer Goods Industry Forum ( Download)
- Ship Faster with GitHub Copilot and Octopus Deploy ( Download)
