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Student Depression Detection with ML

I need a machine learning model to analyze self-reported questionnaires and identify signs of depression among students. The goal is to detect patterns and raise awareness for mental health support. Key Requirements: - Use supervised learning techniques - Implement decision trees as the primary algorithm - Analyze and preprocess survey data - Identify key patterns and indicators of depression - Provide a comprehensive report on findings Ideal Skills and Experience: - Strong background in machine learning, especially supervised learning - Proficiency in decision trees and related algorithms - Experience with data preprocessing and analysis - Ability to generate clear, actionable insights from data

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