SWIFT STUDENT CHALLENGE 2024
-
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.
-
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.
-
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.
-
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.