Resources for Machine Learning practitioners to design, develop, deploy, and maintain ML applications at scale.
Newsletter Issue 17: SQL is dead. Long live SQL. · While I was in college in the 1990s, many of us considered databases as a solved problem. And by...
Newsletter Issue 16: An overview of data pipeline orchestration choices on AWS, Google Cloud, and Azure · You care about the data. Actually, you really...
Newsletter Issue 15: AI research continues to amaze us, but are those safe to use in products and services? Concerns about AI aligning with human goal ·...
Newsletter Issue 14: Data pipelines transport data, ML pipelines transform data before training/inference, MLOps pipelines automate ML workflows. ·...
Newsletter Issue 13: Don't fall for the "AI-first" hype. Focus on being "data-first" and ML/AI will naturally follow. · I learned about this question in...
Newsletter Issue 12: The answer, as usual, is: it depends. · What is MLOps? MLOps stands for Machine Learning Operations. It is a set of practices to...
