Instructions to use amirsoahil101/Iris_Flower_Classification_using_Ensemble_Learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use amirsoahil101/Iris_Flower_Classification_using_Ensemble_Learning with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("amirsoahil101/Iris_Flower_Classification_using_Ensemble_Learning", "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
| # Data Manipulation & Array Computing | |
| numpy>=1.22.0 | |
| pandas>=1.4.0 | |
| # Core Machine Learning Framework | |
| scikit-learn>=1.0.0 | |
| # Ensemble Learning & Advanced Boosting | |
| xgboost>=1.6.0 | |
| # Data Visualization & Exploratory Analysis | |
| matplotlib>=3.5.0 | |
| seaborn>=0.11.2 | |
| # Interactive Development Setup | |
| jupyter>=1.0.0 |