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
It has a really conveniant generic interface that allows comparison of many learning algorithms Alexandre Lacoste
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
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
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
It's a useful, well-maintained, and easy-to-use tool. Fabio Gonzalez
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
I used it for a graduate machine learning course. The code and documentation was an invaluable resource. Shaun Jackman
Scikit-Learn provides with many useful features (learning algorithms, features extraction, hyperparameters selection, etc.) and comes with outstanding documentation. Jean-Francis Roy
Easy to use Big number of algorithms and parametrization possibilities Fast algorithms Remy Vandaele
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
Francis Brochu
Most comprehensive Machine Learning toolkit. In addition, it is easy to use and well documented. Gael Varoquaux
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.