Tabular Regression
Scikit-learn
tabular-classification
machine-learning
random-forest
clustering
k-means
feature-engineering
eda
data-science
predictive-analytics
predictive-modeling
flight-prices
aviation
airlines
travel-tech
tourism
transportation
pricing-optimization
economics
pandas
Eval Results (legacy)
Instructions to use matanzig/flight-price-prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use matanzig/flight-price-prediction with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("matanzig/flight-price-prediction", "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
- Xet hash:
- 9f558961bca612044c47594a1f5bc4568be128c8ff33374f93a142c5d626f07c
- Size of remote file:
- 436 MB
- SHA256:
- 034bad22fdefd7ff58aad1f7fe427a35dc231610ac3b3ed8fcec1b8b8ad9e0c5
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