This is a terminal project I did to earn the Google Advanced Data Analytics Professional Certificate.
The project is divided into two (2) parts:
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Salifort Motors Churn Prediction Model Development
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Waze Churn Prediction Model Development
The goal of the project is to predict which employees are more likely to quit Salifort Motors.
The project is based on a certain HR_capstone_dataset provided in CSV format.
The project was done according to the PACE strategy document provided as a guide.
The technical aspect of the project (the coding) was done in a Python environment.
The findings and insights are provided in an Executive Summary PDF document.
Finally on this, the models employed are saved in the models directory of this repository.
The goal of this project is to predict which users are more likely to churn given the data provided and which features are most important in predicting churn.
The project is based on a certain waze_dataset.csv file
The project is broken into 6 phases:
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Phase 1 - The Project Proposal and PACE Strategy Document for guidelines
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Phase 2 - PACE Strategy Document, lab environment, and Executive Summary
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Phase 3 - PACE Strategy Document, lab environment, and Executive Summary
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Phase 4 - PACE Strategy Document, lab environment, and Executive Summary
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Phase 5 - PACE Strategy Document, lab environment, and Executive Summary
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Phase 6 - PACE Strategy Document, lab environment, and Executive Summary