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handling-missing-values

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Data-Wrangling

This repository contains experiments on data wrangling techniques, focusing on methods for handling missing values, filtering, aggregation, and more.

  • Updated Jan 30, 2025
  • Jupyter Notebook

This project analyzes and preprocesses the Online Retail dataset to uncover insights into customer purchasing behaviors, sales trends, and product performance. It includes data cleaning, exploration, and visualization, with the goal of enhancing understanding of online retail dynamics.

  • Updated Feb 18, 2025
  • Jupyter Notebook

This project implements a machine learning model to predict breast cancer diagnosis. Utilizing techniques such as data preprocessing, feature selection, and various algorithms, the model aims to assist in early detection and improve healthcare outcomes. Explore the repository to understand the methodology and technologies used in this project.

  • Updated Feb 21, 2025
  • Jupyter Notebook

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