Wednesday, January 27, 2021
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ML Projects

Machine Learning Capstone Projects

Predicting Medical Appointment No-Shows

  • Built a supervised ML classification model to predict why 20% of patients fail to appear to their scheduled appointment.
  • Wrote a code using Sklearn’s OneHotEncoder to preprocess the categorical features and convert them to binary vectors.
  • Used a Random Forest model and hyperparameter tuning to improve the ROC score to 0.74.

Analyzing CalCOFI's Oceanographic Trends to Predict Climate Change

  • Built a Supervised ML Regression model to understand oceanographic trends and predict temperature changes.
  • Created a pipeline that fills missing values and scales numeric features.