Engineering on The Probability Enginehttps://carlosdanieljimenez.com/categories/engineering/Recent content in Engineering on The Probability EngineHugo -- 0.147.3en-usSun, 05 Apr 2026 00:00:00 +0000AI Architecture - Notions on Training and Inferencehttps://carlosdanieljimenez.com/post/2026-04-05-ai-architecture-training-inference/Sun, 05 Apr 2026 00:00:00 +0000https://carlosdanieljimenez.com/post/2026-04-05-ai-architecture-training-inference/A technical breakdown of CPU, GPU, TPU, and Edge AI hardware tradeoffs for training and inference workloads — with real-world cost data and a deep dive into Raspberry Pi 5 + Hailo-10H.Anatomy of an MLOps Pipeline - Part 1: Pipeline and Orchestrationhttps://carlosdanieljimenez.com/post/anatomia-pipeline-mlops-part-1-en/Tue, 13 Jan 2026 00:00:00 +0000https://carlosdanieljimenez.com/post/anatomia-pipeline-mlops-part-1-en/Part 1: Philosophy, project architecture and orchestration with Hydra + MLflow. Steps for preprocessing, feature engineering, hyperparameter tuning and model registry.Anatomy of an MLOps Pipeline - Part 2: Deployment and Infrastructurehttps://carlosdanieljimenez.com/post/anatomia-pipeline-mlops-part-2-en/Tue, 13 Jan 2026 00:00:00 +0000https://carlosdanieljimenez.com/post/anatomia-pipeline-mlops-part-2-en/Part 2: CI/CD with GitHub Actions, W&B vs MLflow comparison, complete containerization with Docker, and production-ready API architecture with FastAPI.Anatomy of an MLOps Pipeline - Part 3: Production and Best Practiceshttps://carlosdanieljimenez.com/post/anatomia-pipeline-mlops-part-3-en/Tue, 13 Jan 2026 00:00:00 +0000https://carlosdanieljimenez.com/post/anatomia-pipeline-mlops-part-3-en/Part 3: Model selection strategies, advanced testing, production patterns, data drift, model monitoring, and production readiness checklist.