Introducing G2.ai, the future of software buying.Try now
Product Avatar Image

scikit-learn

Show rating breakdown
59 reviews
  • 1 profiles
  • 1 categories
Average star rating
4.8
Serving customers since
2018

Profile Name

Star Rating

53
6
0
0
0

scikit-learn Reviews

Review Filters
Profile Name
Star Rating
53
6
0
0
0
Palash S.
PS
Palash S.
Graduate Researcher and Freelance data Counsellor in machine learning, data science, and analytics domain.
09/20/2023
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review

Best open source library for Machine learning.

I like how dynamic scikit-learn library is. it provides preloaded and ready-to-use functions for all sorts of machine learning and data preprocessing algorithms.
KS
Kitriakos S.
06/09/2023
Validated Reviewer
Review source: G2 invite
Incentivized Review

scikit-learn

Scikit-learn is built on top of efficient numerical libraries, such as NumPy and SciPy, which provide optimized implementations of mathematical and numerical operations. This ensures that the library can handle large datasets and complex computations efficiently, contributing to its robustness and scalability.
Diana B.
DB
Diana B.
05/02/2023
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review
Translated Using AI

Python library

Users who wish to connect the algorithms to their platforms will find detailed API documentation on the scikit-learn website. Many contributors, authors, and a large international online community support and update Scikit-learn. It is easy to use. The library is published under the BSD license, so it is available for free with only the most basic legal and licensing restrictions. The scikit-learn package is extremely adaptable and useful, and it can be used for a variety of real-world tasks, such as developing neuroimaging, predicting consumer behavior, etc.

About

Contact

HQ Location:
N/A

Social

@scikit_learn

What is scikit-learn?

Scikit-learn is an open-source machine learning library for the Python programming language. It provides simple and efficient tools for data analysis and modeling, making it accessible to both beginners and experienced data scientists. Scikit-learn supports various supervised and unsupervised learning algorithms, including regression, classification, clustering, and dimensionality reduction. It is built on top of other scientific libraries such as NumPy, SciPy, and matplotlib, ensuring seamless integration into the broader Python data science ecosystem. The library emphasizes ease of use, performance, and interoperability, making it a popular choice for developing machine learning applications.

Details

Year Founded
2018