Announcing KeystoneML

Announcing KeystoneML

From the post:

We’ve written about machine learning pipelines in this space in the past. At the AMPLab Retreat this week, we released (live, on stage!) KeystoneML, a software framework designed to simplify the construction of large scale, end-to-end, machine learning pipelines in Apache Spark. KeystoneML is alpha software, but we’re releasing it now to get feedback from users and to collect more use cases.

Included in the package is a type-safe API for building robust pipelines and example operators used to construct them in the domains of natural language processing, computer vision, and speech. Additionally, we’ve included and linked to several scalable and robust statistical operators and machine learning algorithms which can be reused by many workflows.

Also included in the code are several example pipelines that demonstrate how to use the software to reproduce recent academic results in computer vision, natural language processing, and speech processing….

In case you don’t have plans for the rest of the weekend! 😉

Being mindful of Emmett McQuinn’s post, Amazon Machine Learning is not for your average developer – yet, doesn’t mean you have to remain an “average” developer.

You can wait for a cookie cutter solution from Amazon or you can get ahead of the curve. Your call.

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