Recommendation system for mental health support

An intelligent digital mental health platform that analyzes user-generated text using Natural Language Processing techniques to provide personalized psychological insights and recommendations. The system bridges the gap between user emotional expression and actionable guidance through automated analysis and data-driven decision support.

Key Contributions

Implemented NLP-based text analysis to extract emotional patterns and thematic indicators.

Developed a personalized recommendation engine based on user similarity and behavioral patterns.

Technologies

Python, NLP Techniques, Machine Learning Models, Scrapy

System Capabilities

Text-based mental health analysis

Personalized recommendations

Community support integration