Abhi0323/End-to-End-Employee-Churn-Prediction-with-Azure-Databricks

Developed an end-to-end machine learning solution for predicting employee churn using Azure Databricks, leveraging Spark for data processing, MLflow for managing the ML workflow, and deploying the model using Databricks model serving.

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Emerging

This project helps HR and business leaders predict which employees are likely to leave the company. By analyzing your existing employee data, it identifies patterns that lead to churn, providing a list of at-risk individuals. This allows organizations to proactively intervene and retain valuable talent.

No commits in the last 6 months.

Use this if your organization faces significant costs and disruptions from employee turnover and you need a data-driven way to identify and prevent it.

Not ideal if you don't have historical employee data or the resources to act on churn predictions.

HR analytics employee retention talent management workforce planning churn prediction
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 15 / 25

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Stars

9

Forks

5

Language

Jupyter Notebook

License

MIT

Last pushed

May 29, 2024

Commits (30d)

0

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