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:
- af1e2391ca161d7f8308d11251960d65e8eaf80f012cfc37b4562721d9a0f86d
- Size of remote file:
- 125 MB
- SHA256:
- a3a4faba813b09a18d4e0a7e98ebc7a69ee43cdfb60899f86005fb845c90d353
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