[Feature Addition]: Web App for Brain Stroke Prediction

[shravn-10]

ML-Crate Repository (Proposing new issue)

🔴 Project Title : Brain Stroke Prediction with UI and Power BI dashboard
🔴 Aim : Using gradio and streamlit, develop 2 different UI's and a Power BI dashboard which can be used to get better data visualization
🔴 Dataset : full_data.csv

🔴 Approach : Data cleaning , EDA in Power BI dashboard and in ipynb file, using SMOTE to solve class imbalance, Random Forest as it showed highest accuracy and other measures, then building 2 UI's using gradio and streamlit

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📍 Follow the Guidelines to Contribute in the Project :

• You need to create a separate folder named as the Project Title.
• Inside that folder, there will be four main components.
  • Images - To store the required images.
  • Dataset - To store the dataset or, information/source about the dataset.
  • Model - To store the machine learning model you've created using the dataset.
  • requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
• Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

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🔴🟡 Points to Note :

• The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
• "Issue Title" and "PR Title should be the same. Include issue number along with it.
• Follow Contributing Guidelines & Code of Conduct before start Contributing.

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✅ To be Mentioned while taking the issue :

• Full name : Sai Shravan Motamarri
• GitHub Profile Link : shravn-10
• Participant ID (If not, then put NA) : NA
• Approach for this Project : Data cleaning, EDA, class imbalance solving, model training, model evaluation, Developing user interface
• What is your participant role? VSOC contributor

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Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

[github-actions]

Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊

[abhisheks008]

Use the new model implemented in the project folder. Do not create a separate model, use the existing model only.

Assigned @shravn-10

[shravn-10]

Will do