# scikit-learn

#### Machine Learning in Python

Getting Started Release Highlights for 1.3 GitHub

- Simple and efficient tools for predictive data analysis
- Accessible to everybody, and reusable in various contexts
- Built on NumPy, SciPy, and matplotlib
- Open source, commercially usable - BSD license

#### Classification

Identifying which category an object belongs to.

Applications: Spam detection, image recognition. Algorithms: Gradient boosting, nearest neighbors, random forest, logistic regression, and more...

Examples

#### Regression

Predicting a continuous-valued attribute associated with an object.

Applications: Drug response, Stock prices. Algorithms: Gradient boosting, nearest neighbors, random forest, ridge, and more...

Examples

#### Clustering

Automatic grouping of similar objects into sets.

Applications: Customer segmentation, Grouping experiment outcomes Algorithms: k-Means, HDBSCAN, hierarchical clustering, and more...

Examples

#### Dimensionality reduction

Reducing the number of random variables to consider.

Applications: Visualization, Increased efficiency Algorithms: PCA, feature selection, non-negative matrix factorization, and more...

Examples

#### Model selection

Comparing, validating and choosing parameters and models.

Applications: Improved accuracy via parameter tuning Algorithms: grid search, cross validation, metrics, and more...

Examples

#### Preprocessing

Feature extraction and normalization.

Applications: Transforming input data such as text for use with machine learning algorithms. Algorithms: preprocessing, feature extraction, and more...

Examples

#### News

- On-going development: What's new (Changelog)
- October 2023. scikit-learn 1.3.2 is available for download (Changelog).
- September 2023. scikit-learn 1.3.1 is available for download (Changelog).
- June 2023. scikit-learn 1.3.0 is available for download (Changelog).
- March 2023. scikit-learn 1.2.2 is available for download (Changelog).
- January 2023. scikit-learn 1.2.1 is available for download (Changelog).
- December 2022. scikit-learn 1.2.0 is available for download (Changelog).

#### Community

- About us: See authors and contributing
- More Machine Learning: Find related projects
- Questions? See FAQ and stackoverflow
- Subscribe to the mailing list
- Gitter: gitter.im/scikit-learn
- Blog: blog.scikit-learn.org
- Logos & Branding: logos and branding
- Calendar: calendar
- Twitter: @scikit_learn
- LinkedIn: linkedin/scikit-learn
- YouTube: youtube.com/scikit-learn
- Facebook: @scikitlearnofficial
- Instagram: @scikitlearnofficial
- TikTok: @scikit.learn
- Communication on all channels should respect PSF's code of conduct.

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#### Who uses scikit-learn?

"We use scikit-learn to support leading-edge basic research [...]"
"I think it's the most well-designed ML package I've seen so far."
"scikit-learn's ease-of-use, performance and overall variety of algorithms implemented has proved invaluable [...]."
"The great benefit of scikit-learn is its fast learning curve [...]"
"It allows us to do AWesome stuff we would not otherwise accomplish"
"scikit-learn makes doing advanced analysis in Python accessible to anyone."

More testimonials

scikit-learn development and maintenance are financially supported by