Companies that use scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
48,689
companies
List of companies using scikit-learn
curl --request POST \
--url "https://api.theirstack.com/v1/companies/search" \
--header "Accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer <api_key>" \
-d "{
\"company_technology_slug_or\": [
\"scikit-learn\"
]
}"Technology
is any of
scikit-learn
Employees14kRevenue$600MSoftware Developmentscikit-learnHigh confidence
Employees115kHospitals and Health Carescikit-learnHigh confidence
Employees36kRevenue$28BSoftware Developmentscikit-learnHigh confidence
Employees85kRevenue$29BFinancial Servicesscikit-learnHigh confidence
Employees3.2kRevenue$1.2BFinancial Servicesscikit-learnHigh confidence
Employees23kRevenue$3BFinancial Servicesscikit-learnHigh confidence
Employees7Technology, Information and Internetscikit-learnHigh confidence
Employees23kRevenue$957MIT Services and IT Consultingscikit-learnHigh confidence
Employees5.9kRevenue$777MSoftware Developmentscikit-learnHigh confidence
Employees300kRevenue$331BHospitals and Health Carescikit-learnHigh confidence
We have data on 48,689 companies and users that use scikit-learn. Our scikit-learn users and customers list is available for download and comes enriched with vital company specifics, including industry classification, organizational size, geographical location, funding rounds, and revenue figures, among others.
Technology Usage Statistics and Market Share
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Frequently asked questions
Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.
We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.
Scikit-learn is a popular machine learning library in the Python ecosystem known for its user-friendly interface and extensive range of algorithms and tools for data analysis and modeling. It is built on NumPy, SciPy, and Matplotlib, offering a robust framework for machine learning tasks such as classification, regression, clustering, and dimensionality reduction. Scikit-learn is widely used by data scientists, researchers, and machine learning enthusiasts due to its simplicity and efficiency in implementing various algorithms.
PyPI Packages, to which scikit-learn belongs, is a category that encompasses various Python packages available on the Python Package Index (PyPI). These packages cover a wide range of functionalities, including data manipulation, web development, scientific computing, and machine learning. Scikit-learn falls under the machine learning and data analysis subcategory within PyPI Packages, providing essential tools and algorithms for building predictive models and extracting insights from data.
Scikit-learn was founded in 2007 by David Cournapeau as part of the Google Summer of Code project. The motivation behind the creation of scikit-learn was to develop a high-quality machine learning library that is accessible to the Python community and provides a simple yet powerful interface for implementing machine learning algorithms. Over the years, scikit-learn has evolved into one of the most widely used machine learning libraries in the industry, thanks to its active development community and continuous improvements.
Currently, scikit-learn holds a significant market share within the machine learning library category. Its user-friendly interface, extensive documentation, and active community support have contributed to its widespread adoption among both beginners and experienced machine learning practitioners. With the increasing demand for machine learning solutions in various industries, the market share of scikit-learn is expected to continue growing in the future as more companies and individuals leverage its capabilities for data analysis and modeling tasks.