Skip to content

openlearnnitj/capestone-template

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

2 Commits
Β 
Β 

Repository files navigation

Capstone Project 2025

Project Title: Mental Wellness Analysis and Support Strategy

NOTE: Github Repo Name must be Unique OL-ID assigned.


🧾 Student Information

  • Name: Your Name Here
  • Roll No.: Your Roll Number Here
  • OpenLearn ID (OL ID): Your OL ID Here

πŸ“ Project Description

This project aims to understand key factors influencing mental health among tech employees and build data-driven solutions for improving workplace well-being. It uses machine learning techniques to perform classification, regression, and clustering tasks and presents results via an interactive Streamlit dashboard.

Objectives

To understand the key factors influencing mental health issues among employees in the tech industry and build data-driven solutions for:

  • Classification Task: Predict whether an individual is likely to seek mental health treatment.
  • Regression Task: Predict the age of an individual based on personal and workplace attributes, supporting age-targeted intervention design.
  • Unsupervised Task: Segment tech employees into distinct clusters based on mental health indicators to aid in tailored HR policies

πŸ“‚ Project Structure

OL-ID
β”œβ”€β”€ models/ # Machine Learning Models
β”‚ β”œβ”€β”€ classification_model.py
β”‚ β”œβ”€β”€ regression_model.py
β”‚ β”œβ”€β”€ clustering_model.py
β”œβ”€β”€ streamlit/ # Streamlit Application
β”‚ β”œβ”€β”€ app.py
β”‚ β”œβ”€β”€ components.py # UI components (optional)
β”œβ”€β”€ images/ # Screenshots (optional)
β”‚ β”œβ”€β”€ dashboard.png
β”‚ β”œβ”€β”€ eda.png
β”‚ └── model_results.png
β”œβ”€β”€ requirements.txt
└── README.md

πŸ”— Important Links

Demo

Watch the project in action:


Screenshots

  • Dashboard Overview
  • EDA Insights
  • Model Results

Submission Checklist

  • Change the repository name to your OL-ID
  • Fill in Name, Roll No., OL ID
  • Add links for Notebooks, Streamlit App, and Technical Report
  • Upload screenshots in images/
  • Ensure requirements.txt is complete
  • Push models/ and streamlit/ folders with code

Acknowledgements

About

No description, website, or topics provided.

Resources

Code of conduct

Contributing

Stars

Watchers

Forks

Releases

No releases published

Packages