The case for R, for AI developers

April 12, 2018
By

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

I had a great time this week at the Qcon.ai conference in San Francisco, where I had the pleasure of presenting to an audience of mostly Java and Python developers. It's unfortunate that videos won't be available for a while, because there were some amazing presentations: those by Matt Ranney, Mike Williams and Rachel Thomas were particular standouts.

My goal for the presentation I gave was to encourage developers to take a look at R (and its community) for developing AI applications, and in particular to bring a statistical perspective to data, inference and prediction as used by AI applications:

I also delivered a workshop on using R to interface with a couple of the Cognitive Services vision APIs, to generate captions from random images in Wikipedia, and to train a custom image recognizer with images of hotdogs. The workshop is hosted as a Jupyter Notebook, so it's easy to try out yourself — all you need is a browser. You can find all the files and instructions at the link below.

Azure Notebooks: AI for R users 

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