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
Commit ·
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Parent(s): a5cab7d
add requirements.txt file
Browse files- requirements.txt +16 -0
requirements.txt
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# Data Manipulation & Array Computing
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numpy>=1.22.0
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pandas>=1.4.0
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# Core Machine Learning Framework
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scikit-learn>=1.0.0
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# Ensemble Learning & Advanced Boosting
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xgboost>=1.6.0
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# Data Visualization & Exploratory Analysis
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matplotlib>=3.5.0
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seaborn>=0.11.2
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# Interactive Development Setup
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jupyter>=1.0.0
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