Hi all, we recently added factorization machines, core layer to our `nn` library, along with regression and classification scripts.
What is great about it? ------------------------------ 1. The factorization machines handles the cases where SVM fails i.e., where the information is so sparse. 2. In this sparse situation, the algorithm factorizes all the inputs, according to how deep we want to correlate input matrix entries. Factorization Machines are highly scalable, which are already being used at google. If anyone would like to scale them, I am very happy to be involved. Thanks, Janardhan
