How nandot006/machine-health-profiling works
This is an academic machine-learning capstone repository: users run Jupyter notebooks to analyze concrete-strength and machine-maintenance datasets, train models, evaluate them, and export metric summaries. The README documents the regression and classification workflows and their results. Notebook source was not sampled, so internal stages and data flow below reflect README descriptions rather than verified cell-level wiring; clustering is described as a project track but not implemented in Review 1.
Main entry points: 02_Classification_AI4I.ipynb Classification Notebook · 01_Regression_Concrete.ipynb Regression Notebook · concrete_data.csv Concrete Data · ai4i2020.csv AI4I Data
Components 17
Regression Track
- Regression Notebook
notebooks/01_Regression_Concrete.ipynb - EDA & Preparation
notebooks/01_Regression_Concrete.ipynb - Feature Engineering
notebooks/01_Regression_Concrete.ipynb - Regressor Training
notebooks/01_Regression_Concrete.ipynb - Tuning & Validation
notebooks/01_Regression_Concrete.ipynb - Regression Metrics
notebooks/01_Regression_Concrete.ipynb
Classification Track
- Classification Notebook
notebooks/02_Classification_AI4I.ipynb - Sensor Preparation
notebooks/02_Classification_AI4I.ipynb - Feature Engineering
notebooks/02_Classification_AI4I.ipynb - Classifier Training
notebooks/02_Classification_AI4I.ipynb - Classification Metrics
notebooks/02_Classification_AI4I.ipynb
Input Datasets
- Concrete Data
datasets/concrete_data.csv - AI4I Data
datasets/ai4i2020.csv
Metric Outputs
- Regression Results
results/regression_results.csv - Classification Results
results/classification_results.csv - Classification Workbook
results/classification_results.xlsx
Other components
- Project Analyst
Connections 16
- Project Analyst → Regression Notebook: runs
- Concrete Data → Regression Notebook: input data
- Regression Notebook → EDA & Preparation: analyzes
- EDA & Preparation → Feature Engineering: prepares data
- Feature Engineering → Regressor Training: features
- Regressor Training → Tuning & Validation: models
- Tuning & Validation → Regression Metrics: validated models
- Regression Notebook → Regression Results: exports metrics
- Project Analyst → Classification Notebook: runs
- AI4I Data → Classification Notebook: input data
- Classification Notebook → Sensor Preparation: analyzes
- Sensor Preparation → Feature Engineering: prepares data
- Feature Engineering → Classifier Training: features
- Classifier Training → Classification Metrics: predictions
- Classification Notebook → Classification Results: exports metrics
- Classification Notebook → Classification Workbook: exports metrics