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
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README.md
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## 📹 Presentation Video
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<video src=["https://huggingface.co/datasets/
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## 🚀 Interactive Dashboard
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## 📹 Presentation Video
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<video src=["https://huggingface.co/datasets/MichaelYitzchak/Linkedin_Job_Engagement/resolve/main/(https://www.loom.com/share/c7d9b89a54234f699204b16a9a313c7d).mp4] controls style="max-width:720px;"></video>
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---<video src="https://huggingface.co/datasets/MichaelYitzchak/Linkedin_Job_Engagement/resolve/main/(https://www.loom.com/share/c7d9b89a54234f699204b16a9a313c7d).mp4" controls="controls" style="max-width: 720px;"></video>
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## 🚀 Interactive Dashboard
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