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ml-workflows

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AmirhosseinHonardoust / Missing-Data-Doctor

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Missing Data Doctor is a diagnostic and treatment toolkit for missing values in machine learning datasets. It profiles missingness patterns, visualizes gaps, applies multiple imputation strategies, and evaluates their impact on model performance. Includes automated plots, metrics, and a full HTML report.

python data-science machine-learning automation scikit-learn tabular-data eda pandas data-visualization imputation missing-data data-preprocessing feature-engineering data-pipelines data-cleaning data-quality data-profiling ml-engineering data-reporting ml-workflows
  • Updated Nov 15, 2025
  • Python

Abdullah321Umar / DevelopersHub-DataScience-Analytics_Internship-TASK1

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🔴 Predicting Insurance Claim Amounts 🔴 This project analyzes the Medical Cost Personal Insurance Dataset to understand key factors influencing healthcare expenses. Through data cleaning, visualization, and feature engineering, important patterns in age, BMI, smoking, and region were uncovered.

python numpy reporting linear-regression pandas decision-trees scatter-plots heatmaps model-evaluation rmse interpretation mae label-encoding feature-encoding regression-modeling conclusions regression-assumptions ml-workflows line-plots category-comparisons
  • Updated Nov 16, 2025
  • Jupyter Notebook

iTrauco / experiments-test

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DEPRECATED | Minimal sandbox for isolating and testing core machine learning workflow logic across Jupyter notebooks. Used to rebuild clean, reproducible foundations for future MLOps development.

python machine-learning computer-vision experimental jupyter reproducible-research sandbox conda-environment model-training traffic-cameras minimal-example mlops gdot traffic-vision ml-workflows notebook-development workflow-prototyping notebook-isolation georgia-department-of-transportation
  • Updated Jun 23, 2025
  • Jupyter Notebook

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