Scikit-learn
regression
classification
clustering
tabular
linkedin
job-postings
random-forest
decision-tree
kmeans
shap
Instructions to use MichaelYitzchak/Linkedin_Job_Engagement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use MichaelYitzchak/Linkedin_Job_Engagement with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("MichaelYitzchak/Linkedin_Job_Engagement", "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:
- 81fb318d4b3f1c883e6a9afd90d12145316fdf97b99851494ea4ebc0434d3f5a
- Size of remote file:
- 5.79 MB
- SHA256:
- bc0b8ef24e1efe9abd1992a23a2749b5aab18fbef4d8b05d82861b852d498b58
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