Submitted by on Jul 26 2014 } Suggest Revision
From: scikit-learn
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Extensive set of tools for classification, regression, clustering, dimensionality reduction, and model selection, implemented in Python.
Categorized in: Machine Learning | Clustering
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External User
2014-10-30 16:45:05

Its an excellent toolkit for machine learning and data mining. The learning curve makes it ideal for me to teach my data mining class with, while the power also ensures that students can use it later on in in their careers (especially for data wrangling, big data analytics, and data science in general). Dr. Eric C. Larson

External User
2014-10-30 03:01:27

It has a really conveniant generic interface that allows comparison of many learning algorithms Alexandre Lacoste

External User
2014-10-30 02:51:08

My peers and I used this in a somewhat recent academic publication used to predict the best mapping of applications to processors based on their topology and other characteristics. Michael Robson

External User
2014-10-29 23:57:18

Scikit provides a wide variety of Machine Learning and data-processing algorithms, all interfaced through Python. Plus, their website is a great resource for concepts and details about the algorithms. Aaron Berndsen

External User
2014-10-29 19:17:09

Excellent software! Easy to use, good breadth of algorithmic coverage. Helped me in a big way to work on my publications :) Nikhil Jain, CS Grad at UIUC

External User
2014-10-29 17:16:53

It's a useful, well-maintained, and easy-to-use tool. Fabio Gonzalez

External User
2014-10-29 17:09:55

It provides dozens of state of the art classifiers that work well out of the box while still being highly configurable. Being Python-based, it is really easy to write and adapt experiments quickly and concisely and integrate your results with other scientific Python libraries, such as matplotlib. Highly recommended for ML research! David Stevens

External User
2014-10-29 16:51:23

I used it for a graduate machine learning course. The code and documentation was an invaluable resource. Shaun Jackman

External User
2014-10-29 16:44:32

Scikit-Learn provides with many useful features (learning algorithms, features extraction, hyperparameters selection, etc.) and comes with outstanding documentation. Jean-Francis Roy

External User
2014-10-29 15:39:06

Easy to use Big number of algorithms and parametrization possibilities Fast algorithms Remy Vandaele

External User
2014-10-29 15:33:18

Scikit-learn is a great, reliable prototyping tool. In contrast to almost every other library, the documentation is thorough and of tremendously high quality. Chris Dyer

External User
2014-10-29 15:17:48

Francis Brochu

External User
2014-10-28 22:34:44

Most comprehensive Machine Learning toolkit. In addition, it is easy to use and well documented. Gael Varoquaux

Vu Ha
2014-07-10 22:00:25

Sklearn is the perfect tool for rapid modeling on small to medium data. I picked it over R and Weka, and it was a fairly straightforward decision. Advantages include good documentation and the use of Python which is also a general purpose scripting language.