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machine-learning-model

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The aim is to build a predictive model that can accurately classify whether the employee is likely to leave or the employee is likely to stay in the company. This allows companies to take proactive measures, such as improving working conditions, offering promotions, or addressing dissatisfaction, to retain valuable employees.

  • Updated May 26, 2024
  • Jupyter Notebook

Splitting the advertising data (advertising.csv) into training and testing data sets, then choosing and training a classification machine learning algorithm; Getting the accuracy of the ML model; Using feature engineering skills to create new features and improve my ML model;

  • Updated Oct 24, 2023
  • Jupyter Notebook

This project focuses on building a customer churn prediction model using machine learning and visualizing the results with Power BI. You will use Python for churn prediction and Power BI for generating interactive reports that display key metrics such as churn rate, customer demographics, and predictive insights.

  • Updated Oct 3, 2024
  • Python

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