MLOps
Dataiku offers numerous capabilities for implementing a complete MLOps practice:
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The Flow offers full lineage and traceability on the design on models
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Deploying projects to production with full CI/CD capabilities
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Exporting models to Python, Java, MLflow and PMML for scoring outside of DSS
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Comparing models, models versions and behavior of models over time
This section focuses on the following MLOps-specific capabilities:
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Curating features in a Feature Store
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Evaluating and comparing models and model versions
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Analyzing drift
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Importing models from external Machine Learning systems
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Tracking code experiments
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Monitoring projects, endpoints and models health
The Dataiku Academy includes an MLOps Practitioner learning path , and the Knowledge Base has further resources on MLOps and operationalization .