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
Good Read on Artificial Intelligance AI.
Posted by: Arti Kadu | April 17, 2018 at 05:15
When I began learning Data Science / Predictive Analytics, I started off with R and was easily able to understand and use it. But as I started delving into Neural networks / Deep Learning with R, i found a lack of learning resources, as well as community support. Thats why I had to move to Python, and I frankly dont like Python as much as R. I will be more than happy if the R ecosystem around neural networks/ deep learning and other emerging machine learning areas becomes stronger. I will switch back to R, no questions asked.
Posted by: Amit | May 10, 2018 at 03:37
@Amit, you might want to check out RStudio's Tensorflow Gallery. Lots of useful AI and deep learning resources there.
Posted by: David Smith | May 10, 2018 at 09:30