|Photo: Serdar Yegulalp|
|Photo: W.Rebel via Wikimedia|
Over the past year, machine learning has gone mainstream in an unprecedented way. The trend isn't fueled by cheap cloud environments and ever more powerful GPU hardware alone; it’s also the explosion of frameworks now available for machine learning. All are open source, but even more important is how they are being designed to abstract away the hardest parts of machine learning, and make its techniques available to a broad class of developers.
Here’s a baker's dozen machine learning frameworks, either freshly minted or newly revised within the past year. All caught our attention for being a product of a major presence in IT, for attempting to bring a novel simplicity to their problem domain, or for targeting a specific challenge associated with machine learning.