A practical, end-to-end tutorial for generating, evaluating, and governing synthetic data for ML using Python, SDV, and sdmetrics.
Build a production-ready predictive analytics API with Python and FastAPI—training, serving, security, testing, and MLOps in one tutorial.
Build, deploy, and scale a production-ready AI text classification API with Python and FastAPI—training, serving, security, metrics, and monitoring.
Practical guide to AI fraud detection API integration: architecture, payloads, security, thresholds, MLOps, and operations with code samples.
Build a production-grade semantic search with embedding models: data prep, indexing, similarity, hybrid retrieval, re-ranking, evaluation, and scaling.
