Explore foundational concepts of stratified sampling and data splitting in statistics and machine learning. This quiz covers key definitions, practical examples, and best practices to reinforce understanding of effective sampling and creating robust data splits.
Assess your understanding of key model deployment evaluation metrics like latency, throughput, and data drift. This quiz helps reinforce foundational concepts and best practices for measuring and monitoring deployed machine learning models.
Explore your understanding of fairness metrics in machine learning model evaluation with these beginner-friendly questions. Learn key concepts such as disparate impact, demographic parity, equal opportunity, and more to assess ethical and unbiased model performance.
Explore core concepts of out-of-sample and out-of-distribution testing in machine learning and statistics. This quiz helps clarify the differences, objectives, and implications of assessing model generalization in diverse scenarios.
Explore essential concepts of precision, recall, and ROC analysis to evaluate models on imbalanced datasets. This quiz helps reinforce key metrics and reasoning behind their use for fair, reliable machine learning assessment.