Instructions to use Shree8806/ex5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Shree8806/ex5 with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Shree8806/ex5", "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
metadata
tags:
- sklearn
- random-forest
- regression
- mlops-pipeline
Boston Housing Price Prediction Model
This model is trained automatically using GitHub Actions as part of an MLOps CI/CD pipeline.
Model Details
- Algorithm: Random Forest Regressor
- Dataset: Boston Housing
Evaluation Metrics
- MAE: 2.0133
- RMSE: 2.7855
- R2: 0.8942