Getting Started — scikit-learn 1.8.0 documentation
The purpose of this guide is to illustrate some of the main features of scikit-learn. It assumes basic working knowledge of machine learning practices (model fitting, predicting, cross-validation, etc.).
scikit-learn Tutorials — scikit-learn 1.4.2 documentation
Statistical learning: the setting and the estimator object in scikit-learn Supervised learning: predicting an output variable from high-dimensional observations
scikit-learn: machine learning in Python — scikit-learn 1.8.0 …
scikit-learn Machine Learning in Python Getting Started Release Highlights for 1.8
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 …
An introduction to machine learning with scikit-learn
scikit-learn comes with a few standard datasets, for instance the iris and digits datasets for classification and the diabetes dataset for regression. In the following, we start a Python interpreter from our shell …
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.
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 …
Working With Text Data — scikit-learn 1.4.2 documentation
The goal of this guide is to explore some of the main scikit-learn tools on a single practical task: analyzing a collection of text documents (newsgroups posts) on twenty different topics.
13. Choosing the right estimator — scikit-learn 1.8.0 documentation
13. Choosing the right estimator # Often the hardest part of solving a machine learning problem can be finding the right estimator for the job. Different estimators are better suited for different types of data …
13. External Resources, Videos and Talks - scikit-learn
The tutorial covers the basics of machine learning, many algorithms and how to apply them using scikit-learn. Statistical Learning for Text Classification with scikit-learn and NLTK (and slides) by Olivier …