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modeltuning

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lokesh9899 / Mortality-Risk-Readmission-Prediction-NLP-Clinical-Bert-LLM

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AI-powered prediction of in-hospital mortality and 30-day readmission using MIMIC-III clinical data. Combines structured features and ClinicalBERT embeddings with XGBoost/CatBoost Best Performance models for accurate, explainable healthcare forecasting.

visualization python linear-regression transformers xgboost ensemble-learning preprocessing decision-trees feature-engineering catboost bert-embeddings streamlit clinicalbert llms modeltuning
  • Updated May 15, 2025
  • Jupyter Notebook

hashibk / KaggleMallCustomersDataset

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Applied K-Means clustering on Mall Customers dataset with PCA for dimensionality reduction. Cluster labels were added to the dataset and used to train Random Forest and LightGBM classifiers to predict customer segments on new data.

machine-learning random-forest exploratory-data-analysis machine-learning-algorithms eda datascience model-selection lightgbm preprocessing datacleaning mlflow modeltuning
  • Updated Jul 8, 2025
  • Jupyter Notebook

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