Instructions to use KalsusEvening/Melbourne_Housing_Regression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use KalsusEvening/Melbourne_Housing_Regression with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("KalsusEvening/Melbourne_Housing_Regression", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Upload 12 files
Browse files- .gitattributes +3 -0
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- 06_regression_comparison.png +0 -0
- 07_elbow_method.png +3 -0
- 08_cluster_profiles.png +0 -0
- 09_feature_importance.png +0 -0
- 10_classification_comparison.png +0 -0
- 11_class_distribution.png +0 -0
- Assignment_2_Classification,_Regression,_Clustering,_Evaluation_David_Wilfand (2).ipynb +0 -0
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