iaravagni
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Browse files- README.md +2 -2
- glucose_app.py +3 -3
- requirements.txt +0 -0
README.md
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# Blood Glucose Prediction
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# 🩸 Blood Glucose Level Prediction
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This project explores multiple approaches for predicting blood glucose levels using multimodal data from the Big Ideas dataset. It includes data from wearables (accelerometer), nutritional inputs, and demographic/medical history features. Our goal is to evaluate and compare naive, machine learning, and deep learning methods to provide personalized and accurate glucose level forecasts.
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glucose_app.py
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import joblib
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from sklearn.metrics import root_mean_squared_error
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from make_dataset import create_features
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from naive_approach import get_column_specs, prepare_data, zeroshot_eval, simple_diagonal_averaging
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from ml_approach import format_dataset
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SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
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CONTEXT_LENGTH = 52
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import joblib
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from sklearn.metrics import root_mean_squared_error
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from scripts.make_dataset import create_features
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from scripts.naive_approach import get_column_specs, prepare_data, zeroshot_eval, simple_diagonal_averaging
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from scripts.ml_approach import format_dataset
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SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
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CONTEXT_LENGTH = 52
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requirements.txt
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