scikit-learn is a Python library for machine learning built on top of SciPy, providing algorithms and tools for data analysis. It has been maintained since 2007 and is installable as a self-hosted library.
Project overview
The project provides a mature Python module for applying machine learning algorithms and plotting model results.
Project type
Data Processing
Use cases
Data Analysis
Deployment
Refer to project documentation
License
BSD-3-Clause
Best for
Developers, data teams, and researchers working with text and tabular data who need a Python module for machine learning.
Key capabilities
A Python module providing machine learning algorithms and tools built on top of SciPy.
Provides functions starting with plot_ and classes ending with Display for plotting model results.
Limitations and risks
Using this library requires coding in Python.
Getting started
Installation difficulty is documented as easy, assuming dependencies are met. Users can install it using pip install -U scikit-learn.
Alternatives and comparisons
Provides a 12-week, 26-lesson project-based curriculum covering classic machine learning using Scikit-learn.
GitHub project description: scikit-learn: machine learning in Python
README: **scikit-learn** is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.
README: The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and since then many volunteers have contributed. See the `About us <https://scikit-learn.or…
README: Scikit-learn plotting capabilities (i.e., functions start with ``plot_`` and classes end with ``Display``) require Matplotlib (>= |MatplotlibMinVersion|).