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missing-values

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This repository contains a collection of Jupyter Notebook files for various feature engineering techniques, including missing value handling, encoding, transformation, imbalanced dataset, and outlier detection. Each notebook provides practical examples of methods for handling the corresponding problem.

  • Updated May 7, 2023
  • Jupyter Notebook

A classification approach to the machine learning Titanic survival challenge on Kaggle.Data visualisation, data preprocessing and different algorithms are tested and explained in form of Jupyter Notebooks

  • Updated Jun 15, 2023
  • Jupyter Notebook

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