YZ Sözlüğü
Yapay Zekanın tam sözlüğü
CI/CD for ML
Automation of integration and continuous deployment pipelines specific to machine learning models
Model Versioning
Management of ML model versions, associated metadata and artifacts to ensure traceability
Model Monitoring
Continuous monitoring of model performance, metrics, and behavior in production
Feature Store
Centralization and management of features for training and inference of ML models
Data Drift Detection
Identification and analysis of changes in data distribution affecting model performance
Orchestration de Pipelines
Coordination et automatisation des workflows complexes de machine learning de bout en bout
Infrastructure ML
Architecture technique et ressources cloud/on-premise pour héberger et exécuter les modèles ML
Tests Automatisés ML
Validation automatisée des modèles, données et pipelines ML avant mise en production
Gouvernance des Modèles
Cadre de gestion des politiques, conformité et audit des modèles d'intelligence artificielle
Optimisation de Modèles
Techniques d'amélioration des performances et réduction de la complexité des modèles pour la production
A/B Testing pour ML
Méthodologies de test comparatif pour évaluer et déployer de nouvelles versions de modèles
Model Security
Protection of models against adversarial attacks and sensitive data leaks
Explainability ML
Tools and techniques to interpret and explain the decisions of models in production
AutoML in Production
Deployment and maintenance of large-scale automated machine learning systems