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modeldeployment

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The project explores multiple machine learning algorithms and evaluates their performance using various metrics, such as accuracy and confusion matrices. The models tested include Logistic Regression, K-Nearest Neighbors (KNN), Naive Bayes, and Support Vector Machine (SVM). In addition, regularization techniques (L1, L2) are used to avoid overfit.

  • Updated Jan 31, 2025
  • Jupyter Notebook

The Food Delivery Time Prediction Model estimates delivery times using regression algorithms, with XGBoost as the best performer, and is deployed as a real-time application via Streamlit.

  • Updated Oct 13, 2024
  • Jupyter Notebook

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