https://github.com/gokulnpc/calories-burnt-prediction

This web app is created to predict the calories burnt based on the user inputs such as gender, age, height, weight, duration, heart rate, and body temperature. The model used in this web app is a Random Forest Regressor model trained on the dataset with 15000 samples.
https://github.com/gokulnpc/calories-burnt-prediction

machine random-forest-regression regression-models streamlit

Last synced: 9 days ago
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This web app is created to predict the calories burnt based on the user inputs such as gender, age, height, weight, duration, heart rate, and body temperature. The model used in this web app is a Random Forest Regressor model trained on the dataset with 15000 samples.

• Host: GitHub
• URL: https://github.com/gokulnpc/calories-burnt-prediction
• Owner: gokulnpc
• Created: 2024-03-17T13:20:51.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-03-17T13:37:09.000Z (11 months ago)
• Last Synced: 2024-12-07T04:12:16.873Z (2 months ago)
• Topics: machine, random-forest-regression, regression-models, streamlit
• Language: Jupyter Notebook
• Homepage: https://calories-burnt-prediction-app-gokulnpc.streamlit.app/
• Size: 680 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Calories Burnt Prediction

This web app is created to predict the calories burnt based on the user inputs such as gender, age, height, weight, duration, heart rate, and body temperature.

The model used in this web app is a Random Forest Regressor model trained on the dataset with 15000 samples.

The dataset used in this web app is collected from the Kaggle dataset: [Dataset](https://www.kaggle.com/datasets/fmendes/fmendesdat263xdemos).