As I’ve enjoyed Keras for a long time, I was happy to see the launch of Keras 2.0. From a user perspective most of the changes are cosmetic; you still specify layers a line at a time and compile your model using a backend of either Theano or TensorFlow. The one hitch that caught me was that Keras 2.0 needs Theano 0.9 or higher, which hasn’t been released yet. And Theano changed something in their backend about how they internally store convolutional layers. Short story: some of my visualizations broke.

Overall, I still enjoy the library. As I incidentally also upgraded SciPy, I got to realize some speed ups there. I’m excited to hear that Keras 2 is more of an API specification, so supporting more backends and non-Python frontends will be easier in the future. Most likely, though, I’ll keep on using it in Python with Theano for practical machine learning. It makes the implementation easy, letting me focus on the fun part of asking the right question in machine learning.