How to Scaling Out Artifical Neural Networks? I have started to study ANNs with Tensorflow and Keras. Now I want to find a solution to use ANNs over Hadoop. I have learnt that Spark 2.0 does have a Multilayer Perceptron Classifier, but as far as I can see it is quite "primitive" in comparison with TF and Keras (there are only feedforward types and hidden layer/output layer activation functions are hard-wired), there is no wide variety of optimizers, cost functions, architecture types etc.

Is there any competitive alternative for large scale neural networks? Of course, I could use Amazon with very powerful, GPU-driven machines but these are not parallel frameworks either...
You might take a look over TensorFrames, a Databricks library which allow running TensorFlow code on top of Apache Spark : 

https://github.com/databricks/tensorframes