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Medicine_Predictor_with_Streamlit

Medicine Dosage and Prescription Predictor

This project is designed to predict medicine dosage and prescriptions based on input data using machine learning models.

Table of Contents

Forking the Repository

To fork the repository, follow these steps:(forking steps)

  1. Navigate to the repository page on GitHub.
  2. Click the "Fork" button at the top-right corner of the page.
  3. Choose your GitHub account to fork the repository to.

Once you have forked the repository, you can clone it to your local machine:

https://github.com/your-username/Medicine_Predictor_with_streamlit.git
cd Medicine_Predictor_with_streamlit

Installing Dependencies:

pip install -r requirements.txt

Setting Up the Environment:(if required)

python -m venv venv
source venv/bin/activate   # On Windows, use `venv\Scripts\activate`

Running the Project:

python run ml_model.py # To generate new .pkl files for the ML model.
streamlit run app.py

Project Structure

.
├── app.py                     # Main application file
├── Dataset.csv                # Dataset file used for training the models
├── dosage_predictor.pkl       # Pre-trained dosage predictor model
├── label_encoders.pkl         # Label encoders for categorical variables
├── medicine_predictor.pkl     # Pre-trained medicine predictor model
├── ml_model.py                # Script to train and evaluate models
├── requirements.txt           # List of dependencies
└── README.md                  # Project documentation

License

Feel free to adjust any sections to better fit your project's specifics or additional information you would like to include.