Automated Personalized Learning Path Generator

Design a Python-based machine learning system that analyzes student performance data from multiple sources (learning management system, assessment scores, interaction logs) to dynamically generate personalized learning paths. Implement a recommendation algorithm using pandas and scikit-learn that can predict optimal learning sequences, identify knowledge gaps, and suggest targeted interventions. The system should be able to handle diverse data inputs, create individualized curriculum recommendations, and provide probability-weighted learning suggestions with at least 85% accuracy.