jayinai/data-science-question-answer

Provides breadth-focused interview prep across nine ML domains including SQL, statistics, supervised/unsupervised learning, NLP, and systems design—organized as quick-reference Q&A rather than deep tutorials. Covers practical ML fundamentals like cross-validation strategies, feature importance calculations in linear and tree-based models, and a complete project workflow from business objective through production monitoring. Emphasizes hands-on concepts like PySpark for distributed computing and ensemble methods, while encouraging community contributions to expand the knowledge base.

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