Azure/employee-retention-databricks-kubernetes-poc
End-to-end proof of concept showing core MLOps practices to develop, deploy and monitor a machine learning model for an employee retention workload using Databricks and Kubernetes on Microsoft Azure.
This project helps HR teams predict employee turnover by training a machine learning model on historical HR data. It takes in employee information and outputs the likelihood of an employee leaving the organization, alongside insights into data trends and unusual employee profiles. HR managers and business leaders can use this to proactively address retention challenges.
No commits in the last 6 months.
Use this if your organization wants to leverage machine learning to anticipate employee attrition and empower HR with proactive retention strategies.
Not ideal if you're looking for a simple, off-the-shelf HR analytics tool without needing to manage a dedicated machine learning infrastructure.
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15
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11
Language
Bicep
License
MIT
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Last pushed
May 28, 2024
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