Effective machine learning (ML) now demands not just building models but deploying and managing them at scale. Written by a seasoned senior software engineer with high-level expertise in both MLOps ...

In the last lecture, you learned about branching and setting up a CI pipeline in GitHub Actions. Now we’ll take it a step further: once your code passes tests, it should also be deployed automatically ...

MLOps, or DevOps for machine learning, is bringing the best practices of software development to data science. You know the saying, “Give a man a fish, and you’ll feed him for a day… Integrate machine ...

Locking down AI pipelines in Azure? A zero-trust, metadata-driven setup makes it secure, scalable and actually team-friendly. AI pipelines are transforming how enterprises handle data, but they’re ...

Who needs rewrites? This metadata-powered architecture fuses AI and ETL so smoothly, it turns pipelines into self-evolving engines of insight. In the fast-evolving landscape of enterprise data ...