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8. Computing with scikit-learn — scikit-learn 1...
Strategies to scale computationally: bigger data- Scaling with instances using out-of-core learning., Computational Performance- Prediction Latency, Prediction Throughput, Tips and Tricks., Paralle...scikit-learn.org/stable/computing.html -
2.8. Density Estimation — scikit-learn 1.6.1 do...
Density estimation walks the line between unsupervised learning, feature engineering, and data modeling. Some of the most popular and useful density estimation techniques are mixture models such as...scikit-learn.org/stable/modules/density.html -
Model-based and sequential feature selection — ...
This example illustrates and compares two approaches for feature selection: SelectFromModel which is based on feature importance, and SequentialFeatureSelector which relies on a greedy approach. We...scikit-learn.org/stable/auto_examples/feature_selection/plot_select_from_model_diabetes.html -
L1-based models for Sparse Signals — scikit-lea...
The present example compares three l1-based regression models on a synthetic signal obtained from sparse and correlated features that are further corrupted with additive gaussian noise: a Lasso;, a...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_and_elasticnet.html -
Plot different SVM classifiers in the iris data...
Comparison of different linear SVM classifiers on a 2D projection of the iris dataset. We only consider the first 2 features of this dataset: Sepal length, Sepal width. This example shows how to pl...scikit-learn.org/stable/auto_examples/svm/plot_iris_svc.html -
Getting Started — scikit-learn 1.6.1 documentation
The purpose of this guide is to illustrate some of the main features that scikit-learn provides. It assumes a very basic working knowledge of machine learning practices (model fitting, predicting, ...scikit-learn.org/stable/getting_started.html -
Frozen Estimators — scikit-learn 1.6.1 document...
Examples concerning the sklearn.frozen module. Examples of Using FrozenEstimatorscikit-learn.org/stable/auto_examples/frozen/index.html -
Nearest Neighbors — scikit-learn 1.6.1 document...
Examples concerning the sklearn.neighbors module. Approximate nearest neighbors in TSNE Caching nearest neighbors Comparing Nearest Neighbors with and without Neighborhood Components Analysis Dimen...scikit-learn.org/stable/auto_examples/neighbors/index.html -
Cross decomposition — scikit-learn 1.6.1 docume...
Examples concerning the sklearn.cross_decomposition module. Compare cross decomposition methods Principal Component Regression vs Partial Least Squares Regressionscikit-learn.org/stable/auto_examples/cross_decomposition/index.html -
Release Highlights — scikit-learn 1.6.1 documen...
These examples illustrate the main features of the releases of scikit-learn. Release Highlights for scikit-learn 1.6 Release Highlights for scikit-learn 1.5 Release Highlights for scikit-learn 1.4 ...scikit-learn.org/stable/auto_examples/release_highlights/index.html