Blog

A practical 8-week roadmap for mastering the full MLOps lifecycle—data versioning, experiment tracking, model APIs, monitoring, and CI/CD pipelines—using only free, local, open-source tools.

Dive into the AUROC metric—its mathematical foundation, interpretation, and practical pros and cons in evaluating binary classification models.

A rigorous mathematical decomposition of prediction error into bias, variance, and irreducible noise—with practical intuitions on how to balance them for better-generalizing models.

DeepSeek-GRM introduces Self-Principled Critique Tuning (SPCT) and inference-time scaling to create flexible, accurate reward models that rival much larger LLMs in generalist evaluation tasks.

A study exploring the faithfulness of chain-of-thought (CoT) in reasoning models.