AWS vs Azure for Machine Learning: How to Choose the Right Cloud Platform? скачать в хорошем качестве

AWS vs Azure for Machine Learning: How to Choose the Right Cloud Platform?

A comprehensive comparison of AWS vs. Azure: which cloud ML platform should you use for scalable training jobs and real-world MLOps? In this video, we break down how Azure Machine Learning and AWS SageMaker handle project setup, data storage, compute, and environments so you can choose the right platform for your team’s workflows. 🗒️ Full guide with code snippets: part 1: https://towardsdatascience.com/azure-... part 2: https://towardsdatascience.com/aws-vs... ​ Chapter: 01:35 Project setup & permission management (RBAC vs. AWS IAM) 05:17 Data storage (Datastore vs. AWS S3) 08:06 Compute (Persistent compute; AWS SageMaker spot instance) 12:44 Runtime environments (Azure ML curated vs custom; SageMaker built-in/script/BYOC) 15:27 Comparison Summary ​​ 🎬 If you want to build video like this using Hera AI, get 15% off using this link: https://hera.cello.so/gpjkXUu6nk2 ☕ Follow us on Substack for weekly, byte-sized data science articles. Support our channel: https://buymeacoffee.com/visualdesign Substack: https://substack.com/@datavisualdesign X: https://x.com/GongDestin Towards Data Science: https://towardsdatascience.com/author...