Connecting R to Keras and TensorFlow by Joseph Rickert.
From the post:
It has always been the mission of R developers to connect R to the “good stuff”. As John Chambers puts it in his book Extending R:
One of the attractions of R has always been the ability to compute an interesting result quickly. A key motivation for the original S remains as important now: to give easy access to the best computations for understanding data.
From the day it was announced a little over two years ago, it was clear that Google’s TensorFlow platform for Deep Learning is good stuff. This September (see announcment), J.J. Allaire, François Chollet, and the other authors of the keras package delivered on R’s “easy access to the best” mission in a big way. Data scientists can now build very sophisticated Deep Learning models from an R session while maintaining the flow that R users expect. The strategy that made this happen seems to have been straightforward. But, the smooth experience of using the
KerasAPI indicates inspired programming all the way along the chain from TensorFlow to R.
…
The Redditor deepfakes, of AI-Assisted Fake Porn fame mentions Keras as one of his tools. Is that an endorsement?
Rickert’s post is a quick start to Keras and Tensorflow but he does mention:
the MEAP from the forthcoming Manning Book, Deep Learning with R by François Chollet, the creator of Keras, and J.J. Allaire.
I’ve had good luck with Manning books in general so am looking forward to this one as well.