EarthGuard

SWIFT STUDENT CHALLENGE 2024 

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1. Model Creation with CreateML:

   • EarthGuard utilizes CreateML to develop machine learning models.
   • CreateML simplifies the process of training models using user-provided datasets.
   • Models are tailored to specific tasks such as predicting CO2 emissions and water/sanitation scores.

2. Prediction with CoreML:

   • CoreML integration enables efficient prediction within the EarthGuard app.
   • CoreML's optimized performance ensures fast and accurate predictions.
   • Users input relevant data, such as car details or country-year combinations, for predictions.

3. User Input and Interaction:

   • Users interact with EarthGuard by providing input for prediction tasks.
   • Input parameters vary based on the prediction task, such as car details or country-year combinations.
   • EarthGuard's user interface guides users through the input process for seamless interaction.

4. Environmental Awareness and Sustainability:

   • EarthGuard's core objective is to promote environmental awareness and sustainability.
   • By providing insights into CO2 emissions and water/sanitation scores, EarthGuard empowers users to make eco-conscious decisions.
   • The app's continuous improvement reflects its commitment to advancing environmental consciousness and sustainability efforts.

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