https://github.com/sreyashidey/ai-campaign

A streamlit app
https://github.com/sreyashidey/ai-campaign

python sckit-learn streamlit

Last synced: about 1 month ago
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A streamlit app

• Host: GitHub
• URL: https://github.com/sreyashidey/ai-campaign
• Owner: Sreyashidey
• Created: 2025-03-13T17:18:28.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-03-13T17:23:10.000Z (over 1 year ago)
• Last Synced: 2025-03-21T22:17:51.493Z (over 1 year ago)
• Topics: python, sckit-learn, streamlit
• Language: Python
• Homepage: https://ai-campaign-1.streamlit.app/
• Size: 114 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          

## Doctor Activity Predictor

##  Overview

The **Doctor Activity Predictor** is a **machine learning-powered web application** that predicts which doctors are most likely to take a survey at a given time. Users input a time (e.g., `"06:00"`), and the app generates an **Excel file** containing a list of NPIs (doctor IDs) who are predicted to be active.

##  Features

 **Machine Learning Model**: Uses a trained `RandomForestClassifier` to predict active doctors.  

 **User-Friendly Web Interface**: Built with **Streamlit** for easy interaction.  

 **Excel File Export**: Downloads the results in `.xlsx` format.  

 **Real-Time Predictions**: Users can input any time and get instant results.  

  

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##  Project Structure

```

Doctor-Activity-Predictor/

│── model.pkl                 # Trained Machine Learning model

│── dummy_npi_data.xlsx        # Dataset (Excel format)

│── main.py                    # Streamlit web app

│── doctors.py                 # Model training script (from Colab)

│── README.md                  # Documentation (this file)

│── requirements.txt            # List of dependencies