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  1. scikit-learn: machine learning in Python — scikit-learn 1.8.0 …

    scikit-learn Machine Learning in Python Getting Started Release Highlights for 1.8

  2. Installing scikit-learn — scikit-learn 1.8.0 documentation

    Install the version of scikit-learn provided by your operating system or Python distribution. This is a quick option for those who have operating systems or Python distributions that distribute scikit-learn.

  3. API Reference — scikit-learn 1.8.0 documentation

    This is the class and function reference of scikit-learn. Please refer to the full user guide for further details, as the raw specifications of classes and functions may not be enough to give full guidelines …

  4. User Guide — scikit-learn 1.8.0 documentation

    Jan 1, 2010 · 9. Computing with scikit-learn 9.1. Strategies to scale computationally: bigger data 9.1.1. Scaling with instances using out-of-core learning 9.2. Computational Performance 9.2.1. Prediction …

  5. Examples — scikit-learn 1.8.0 documentation

    This is the gallery of examples that showcase how scikit-learn can be used. Some examples demonstrate the use of the API in general and some demonstrate specific applications in tutorial form.

  6. train_test_split — scikit-learn 1.8.0 documentation

    Gallery examples: Image denoising using kernel PCA Faces recognition example using eigenfaces and SVMs Model Complexity Influence Prediction Latency Lagged features for time series forecasting …

  7. 1. Supervised learning — scikit-learn 1.8.0 documentation

    Jan 1, 2010 · Linear Models- Ordinary Least Squares, Ridge regression and classification, Lasso, Multi-task Lasso, Elastic-Net, Multi-task Elastic-Net, Least Angle Regression, LARS Lasso, Orthogonal …

  8. GaussianMixture — scikit-learn 1.8.0 documentation

    Gallery examples: Comparing different clustering algorithms on toy datasets Demonstration of k-means assumptions Gaussian Mixture Model Ellipsoids GMM covariances GMM Initialization Methods …

  9. KMeans — scikit-learn 1.8.0 documentation

    Empirical evaluation of the impact of k-means initialization Comparison of the K-Means and MiniBatchKMeans clustering algorithms Release Highlights for scikit-learn 0.23 Release Highlights …

  10. 1.17. Neural network models (supervised) - scikit-learn

    In particular, scikit-learn offers no GPU support. For much faster, GPU-based implementations, as well as frameworks offering much more flexibility to build deep learning architectures, see Related Projects.