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Last updated : Nov 30, 2017
Not on the current edition
This blip is not on the current edition of the Radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar Understand more
Nov 2017
Trial ? Worth pursuing. It is important to understand how to build up this capability. Enterprises should try this technology on a project that can handle the risk.

Scikit-learn is not a new tool (it is approaching its tenth birthday); what is new is the rate of adoption of machine-learning tools and techniques outside of academia and major tech companies. Providing a robust set of models and a rich set of functionality, Scikit-learn plays an important role in making machine-learning concepts and capabilities more accessible to a broader (and often non-expert) audience.

Nov 2016
Assess ? Worth exploring with the goal of understanding how it will affect your enterprise.

Scikit-learn is an increasingly popular machine-learning library written in Python. It provides a robust set of machine-learning models such as clustering, classification, regression and dimensionality reduction, and a rich set of functionality for companion tasks like model selection, model evaluation and data preparation. Since it is designed to be simple, reusable in various contexts and well documented, we see this tool accessible even to nonexperts to explore the machine-learning space.

Published : Nov 07, 2016
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