Selected work Personal project
Exploring predictive maintenance with engine data.
A personal predictive-maintenance project using the NASA C-MAPSS dataset, machine learning and dashboards.
- Discipline
- Machine learning / Predictive analytics
- Context
- Personal project
- Approach
- Python / NASA C-MAPSS / XGBoost
Original illustrative process view. This is a visual explanation, not a client screenshot or a measured result.
The context.
The NASA C-MAPSS dataset provides a setting for exploring predictive maintenance from engine data. This personal project combined model development with a way to inspect the resulting analysis.
Inside the approach.
- Used Python to work with NASA C-MAPSS data.
- Explored XGBoost and Random Forest models for the predictive-maintenance task.
- Included Docker and dashboards in the project workflow.
What came out of it.
An end-to-end personal exploration of maintenance prediction, model workflows and analytical presentation.
Working through something similar? Bring the problem, the existing system, or the early idea. We can explore a useful next step.
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