Comprehensive Machine Learning Portfolio: Real-world data science, classification, regression, and business analytics in Python
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Updated
Oct 27, 2025 - Jupyter Notebook
Comprehensive Machine Learning Portfolio: Real-world data science, classification, regression, and business analytics in Python
End-to-end tabular ML pipeline: example dataset + single script to train and evaluate all models, SHAP explainability, and cross-model consistency analysis.
This comprehensive course covers the fundamental concepts and practical techniques of Scikit-learn, the essential machine learning library in Python. Learn to build, train, and evaluate machine learning models using various algorithms and preprocessing techniques.
Comprehensive AutoML framework that automates data preprocessing, feature engineering, model selection, hyperparameter tuning, and deployment. Features neural architecture search and automated data cleaning pipelines.
🔍 Streamline tabular binary classification with model interpretability and SHAP consistency analysis for clear insights and robust evaluation.
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