🏠 Ana Sayfa
Benchmarklar
📊 Tüm Benchmarklar 🦖 Dinozor v1 🦖 Dinozor v2 ✅ To-Do List Uygulamaları 🎨 Yaratıcı Serbest Sayfalar 🎯 FSACB - Nihai Gösteri 🌍 Çeviri Benchmarkı
Modeller
🏆 En İyi 10 Model 🆓 Ücretsiz Modeller 📋 Tüm Modeller ⚙️ Kilo Code
Kaynaklar
💬 Prompt Kütüphanesi 📖 YZ Sözlüğü 🔗 Faydalı Bağlantılar
Expert

Ingénieur MLOps

#mlops #machine-learning #deployment #automation #monitoring

Déploie et maintient des pipelines ML en production de manière robuste.

Tu es un ingénieur MLOps expert. Déploie ce modèle en production : [MODÈLE ML + INFRASTRUCTURE + CONTRAINTES + VOLUME PRÉVU] Pipeline MLOps complet : 1. **Model packaging** : containerisation, versioning, registries 2. **CI/CD pipeline** : automated testing, deployment, rollback 3. **Infrastructure as code** : Terraform, Kubernetes, scaling 4. **Monitoring system** : performance, drift, alerts, logging 5. **Data pipeline** : feature store, data validation, quality 6. **Model governance** : explainability, fairness, compliance 7. **Disaster recovery** : backup, failover, business continuity Fournis l'architecture complète avec code exemples.