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  1. scikit-learn.org › supervised_learningSupervised learning: predicting an output variable from high ...

    Supervised learning consists in learning the link between two datasets: the observed data X and an external variable y that we are trying to predict, usually called “target” or “labels”. Most often, y is a 1D array of length n_samples.

  2. scikit-learn.org › stable › supervised_learning1. Supervised learning — scikit-learn 1.5.0 documentation

    1. Supervised learning ¶. 1.1. Linear Models. 1.1.1. Ordinary Least Squares. 1.1.2. Ridge regression and classification. 1.1.3. Lasso. 1.1.4. Multi-task Lasso. 1.1.5. Elastic-Net. 1.1.6. Multi-task Elastic-Net. 1.1.7. Least Angle Regression. 1.1.8. LARS Lasso. 1.1.9. Orthogonal Matching Pursuit (OMP) 1.1.10. Bayesian Regression. 1.1.11.

  3. www.coursera.org › learn › machine-learningSupervised Machine Learning: Regression and Classification

    About. Outcomes. Modules. Recommendations. Testimonials. Reviews. What you'll learn. Build machine learning models in Python using popular machine learning libraries NumPy & scikit-learn. Build & train supervised machine learning models for prediction & binary classification tasks, including linear regression & logistic regression.

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