Absolutely! Here's the GitHub README file written in Markdown syntax:
This project utilizes machine learning to predict calories burnt during exercise, leveraging a web interface built with Streamlit.
Python 3.x Required packages: numpy scikit-learn pickle warnings streamlit Install these packages using pip:
pip install numpy scikit-learn pickle warnings streamlit
Clone this repository:
git clone https://github.com/your-username/calories-burnt-prediction.git
cd calories-burnt-prediction
streamlit run streamlit_app.py
In the web interface, select your gender and provide the following information:
Age (years) Height (cm) Weight (kg) Duration of exercise (minutes) Average heart rate (beats per minute) Average body temperature (Celsius) Click the "Calculate the calories burnt during exercise" button to see the prediction.
X_train, X_test: These datasets contain the features used for training and testing the model (e.g., gender, age, height, etc.). TrainedModel.sav: The serialized machine learning model.