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When preparing for a data scientist interview, it is crucial to understand the importance of assessing model performance using techniques like train/test split and cross-validation. These methods help determine how well a model generalizes to unseen data, which is vital for real-world applications. Before diving into solutions, clarifying the requirements involves:
Understanding the Objective:
Identifying Key Concepts:
Defining Success Criteria:
Gathering Requirements:
Assessing Potential Challenges: