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Core
Topological Sort and DAGs
A topological sort orders the nodes of a directed acyclic graph so that every edge points forward, which is exactly what dependency resolution needs. Kahn's algorithm peels off zero-indegree nodes while DFS post-order reverses the finish times, and both detect cycles for free when no valid order exists. Applied-AI interviews probe it because build systems, data pipelines, and task schedulers are dependency graphs, and the course-schedule question is its canonical disguise.
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RELATED CONCEPTS
PRACTICE THIS IN REAL QUESTIONS
Coding & DSATopological sort: order tasks with dependencies (and detect cycles).→Coding & DSACourse Schedule: can you finish all courses given prerequisites (cycle detection)?→Coding & DSABuild a spreadsheet cell-dependency engine: evaluate formulas and detect circular references.→Coding & DSAExplain BFS and DFS and when to use each, then detect a cycle in a graph.→MLOps & ML EngineeringHow do you orchestrate ML pipelines (Airflow, Kubeflow, etc.), and what makes ML pipelines special?→MLOps & ML EngineeringWhat DAG design patterns make an ML orchestration pipeline reliable in Airflow or Dagster?→
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