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scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
12,700
companies
Technology
is any of
scikit-learn
Company | Country | Industry | Employees | Revenue | Technologies |
---|---|---|---|---|---|
United States | Software Development | 8.9K | $600M | ![]() scikit-learn | |
United States | Software Development | 194 | $6M | ![]() scikit-learn | |
United Kingdom | Technology, Information And Internet | 604 | $5.3M | ![]() scikit-learn | |
United States | Software Development | 5.8K | $777M | ![]() scikit-learn | |
United States | Software Development | 8.5K | $2.2B | ![]() scikit-learn | |
Canada | Software Development | 34K | $6.6B | ![]() scikit-learn | |
United States | Software Development | 28K |
| ![]() scikit-learn | |
It Services And It Consulting |
| ![]() scikit-learn | |||
United States | Business Consulting And Services | 2K | $33M | ![]() scikit-learn | |
Canada | It Services And It Consulting | 71 | $11M | ![]() scikit-learn | |
United States | Financial Services | 2.6K | $1.2B | ![]() scikit-learn | |
United States | Insurance | 440 | $13M | ![]() scikit-learn |
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scikit-learn is used in 96 countries
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.
You can access an updated list of companies using scikit-learn by visiting TheirStack.com. Our platform provides a comprehensive database of companies utilizing various technologies and internal tools.
As of now, we have data on 12,700 companies that use scikit-learn.
scikit-learn is used by a diverse range of organizations across various industries, including "Software Development", "Software Development", "Technology, Information And Internet", "Software Development", "Software Development", "Software Development", "Software Development", "It Services And It Consulting", "Business Consulting And Services", "It Services And It Consulting". For a comprehensive list of all industries utilizing scikit-learn, please visit TheirStack.com.
Some of the companies that use scikit-learn include Databricks, Very, Faculty, Tripadvisor, Veeva Systems, Thomson Reuters, Nielsen, Metiora, Tredence, Ample Insight Inc. and many more. You can find a complete list of 12,700 companies that use scikit-learn on TheirStack.com.
Based on our data, scikit-learn is most popular in United States (3,642 companies), United Kingdom (785 companies), Germany (405 companies), India (377 companies), France (317 companies), Canada (301 companies), Spain (254 companies), Brazil (173 companies), Netherlands (109 companies), Australia (96 companies). However, it is used by companies all over the world.
You can find companies using scikit-learn by searching for it on TheirStack.com, We track job postings from millions of companies and use them to discover what technologies and internal tools they are using.
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