MLOps
MLOps (Machine Learning Operations) is a set of practices, culture, and tools focused on automating and unifying the lifecycle of machine learning models, spanning data collection, training, testing, deployment, and monitoring.
Frequently Asked Questions
How does MLOps differ from DevOps?▼
DevOps focuses on code versioning and software deployment. MLOps deals with three axes: code versioning, dataset versioning, and model weight parameters, which are non-deterministic and decay over time.
What is model drift in MLOps?▼
Model drift occurs when the statistical properties of production input data change over time relative to the training data, leading to a decay in prediction accuracy and requiring retraining.
Quick Facts
- CategoryModel Operations
- Key ApplicationAutomated CI/CD model pipelines, prediction monitoring dashboards, and model registry management.
Coverage Trend12 Weeks
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MLOps Media Coverage & Intelligence
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