Machine Learning Operations (MLOps) Flashcards
7 cards from real AIF-C01 practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Machine Learning Operations (MLOps) flashcards as text
What is the primary goal of MLOps?
Answer: To streamline the end-to-end lifecycle of ML models from development to production
MLOps combines ML, DevOps, and data engineering practices to standardize and automate the full ML lifecycle including building, deploying, and monitoring models.
Which type of drift occurs when the statistical properties of the input features change over time?
Answer: Data drift
Data drift (also called feature drift or covariate shift) refers to changes in the statistical properties of model input features compared to the training data.
What AWS service provides a central repository to catalog, version, and manage ML models?
Answer: Amazon SageMaker Model Registry
Amazon SageMaker Model Registry allows teams to catalog models, manage model versions, associate metadata, and control model approval status for deployment.
In a CI/CD pipeline for ML, what does 'CT' (Continuous Training) specifically refer to?
Answer: Automatically retraining models when new data or triggers are detected
Continuous Training (CT) automatically re-triggers the model training pipeline when new data arrives, performance degrades, or scheduled intervals occur.
What is the purpose of a baseline in Amazon SageMaker Model Monitor?
Answer: To define the expected statistical properties of input data and model outputs for comparison
A baseline captures statistics and constraints from the training data so Model Monitor can compare live inference data against it to detect drift and violations.
Which deployment strategy sends a small percentage of live traffic to a new model version while the majority goes to the existing version?
Answer: Canary deployment
Canary deployment routes a small slice of production traffic (e.g., 5%) to the new model version, allowing real-world validation before a full rollout.
What does Amazon SageMaker Pipelines provide?
Answer: An orchestration tool for automating and reproducing end-to-end ML workflows
SageMaker Pipelines is a purpose-built CI/CD service for ML that lets you define, automate, and track each step of the ML workflow as a directed acyclic graph (DAG).