Category: MLOps & Deployment
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MLOps Cheat Sheet: 12 Production Patterns You’ll Use
12 MLOps patterns from production systems: feature caching, traffic shadowing, schema validation. Real code, not theory.
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Model Drift Detection Failed Silently: Evidently AI Fix
Fix Evidently AI's silent drift detection failures with schema validation. Real production errors, Wasserstein metrics, and monitoring setup.
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Triton vs TorchServe: How I Cut $800/Month in GPU Costs
Triton cut my inference costs 52% vs TorchServe. GPU utilization jumped from 23% to 81%. Here's what profiling actually revealed.
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MLflow + FastAPI: $2K/Month Model Serving Side Project
MLflow tracking + FastAPI serving generates $2K/month from gradient boosting churn models. Real architecture, deployment costs included.
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Gold Price Prediction: Jupyter Notebook to REST API
Build production gold price API with model versioning, drift detection, and monitoring. From Jupyter notebook to deployment in 7 steps.
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DVC vs MLflow: Data Versioning and Model Registry Compared
DVC tracks data pipelines with Git commits. MLflow logs experiments and serves models. Compare both with real codeโchoose the right tool.
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Building a Credit Risk Scoring Model with Machine Learning
Build a credit scoring model with XGBoost: 0.92 AUC-ROC achieved. SHAP explainability, feature engineering, and production deployment guide.
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Smart Factory AI Pipeline: End-to-End Case Study
Smart factory AI that survives edge throttling and RL constraints: 3 deployment fixes from thermal crashes to scheduler violations.