Portfolio Details

Each project in this portfolio reflects my hands-on experience in solving real-world problems using data science, machine learning, and full-stack development. From predictive models to intelligent web applications, these solutions are built with a focus on scalability, functionality, and impact.

Project Information

  • Project Name: Healthcare WebApp
  • Category: AI-Powered Mental Health Analyzer
  • Model Type: NLP with Sentence Transformers
  • Github Repo: Link

Technologies Used

This project is built using Python and Flask on the backend, with a modern frontend powered by Next.js and Firebase. It leverages NLP techniques and sentence-transformers to understand user sentiment and classify emotional states such as stress, anxiety, and depression. Firebase is used for real-time analytics, authentication, and data storage.

Details of Project

The Mental Health Analyzer is a key feature of the AI-powered Healthcare WebApp. It enables users to type out their thoughts and receive instant analysis of their emotional state—detecting patterns of stress, anxiety, depression, or general well-being. The system is powered by a sentence-transformer model trained for semantic understanding, delivering accurate and human-like feedback.

Designed with both accessibility and sensitivity in mind, the analyzer ensures that users feel supported while maintaining strict data privacy through Firebase integration. It's a step toward using AI to support mental well-being and emotional awareness in digital healthcare.

Project Features

  • Analyzes user-written text to detect emotional states using NLP.
  • Built with sentence-transformers for contextual understanding.
  • Secure user data handling through Firebase authentication.
  • Real-time feedback with a responsive and clean UI.
  • Backed by a scalable Flask API integrated with AI services.