Machine Learning Quiz – PART 1

This QUIZ evaluates foundational knowledge of machine learning, focusing on core concepts, learning paradigms, and essential terminology.

Learners are assessed on supervised, unsupervised, and reinforcement learning approaches, including classification, regression, clustering, and dimensionality reduction.

The QUIZ QUESTIONS also covers model complexity, bias–variance trade-offs, feature engineering, and fundamental evaluation metrics.

By the end of this part, learners should demonstrate a solid conceptual understanding of how machine learning models are formulated, trained, and evaluated in practice.

Key Topics Covered:

• Machine learning definitions and domain layers
• Learning paradigms (supervised, unsupervised, reinforcement)
• Classification, regression, and clustering tasks
• Bias–variance trade-off and overfitting/underfitting
• Feature scaling, encoding, and dimensionality reduction
• Model evaluation metrics and validation strategies