Tabular Regression
Scikit-learn
English
melbourne-housing
real-estate
price-prediction
classification
regression
clustering
random-forest
gradient-boosting
tabular
feature-engineering
supervised-learning
kmeans
Instructions to use 0tizm0/melbourne-price-winner-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use 0tizm0/melbourne-price-winner-model with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("0tizm0/melbourne-price-winner-model", "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
Itai Morag commited on
Upload itai_Assignment_2_Classification,_Regression,_Clustering,_Evaluation.ipynb
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itai_Assignment_2_Classification,_Regression,_Clustering,_Evaluation.ipynb
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