https://github.com/kumaarbalbir/porosity-prediction-of-rocks-using-ml
The manual laboratory measurement of porosity of rocks on thermal treatment is tedious and time consuming. We can ease this task by building a predictive model trained on physical features of rocks samples.
https://github.com/kumaarbalbir/porosity-prediction-of-rocks-using-ml
knn-algorithm linear-regression machine-learning-algorithms mineral-exploration python3 random-forest rocks svm-regressor xgboost-algorithm
Last synced: 28 days ago
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The manual laboratory measurement of porosity of rocks on thermal treatment is tedious and time consuming. We can ease this task by building a predictive model trained on physical features of rocks samples.
- Host: GitHub
- URL: https://github.com/kumaarbalbir/porosity-prediction-of-rocks-using-ml
- Owner: KumaarBalbir
- Created: 2023-04-04T08:56:30.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-04-04T08:58:54.000Z (about 2 years ago)
- Last Synced: 2023-04-04T10:15:41.236Z (about 2 years ago)
- Topics: knn-algorithm, linear-regression, machine-learning-algorithms, mineral-exploration, python3, random-forest, rocks, svm-regressor, xgboost-algorithm
- Language: Jupyter Notebook
- Homepage:
- Size: 3.85 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0