TFLearn

The best thing related to TFLearn is it have inbuilt functions for all the machine learning functions and equations in a single line of code most of the time. Therefore I feel like it is the best rapid prototyping tool that can be used to develop fast deep learning models. The next best thing that I love is TFlearn has not of tutorials and backup support. The matrix operations are handled by the Tensorflow developed by Google. The TFLearn runs on top of Tensorflow. The next best thing is that it supports normal CPU operation and also the GPU operation. It runs very fast on CUDA cored GPU. Easy to test models on different devices.

A good higher level abstraction for using deep learning models out of the box. Saves the headache of having to create a manual configuration from scratch in tensorflow (other than if you want to use the Estimator API, which isn't that configurable). If I need to test a new architecture for my business-case, this can easily spin up one for me, the default configurations are quite usable.

simple abstraction on tensorflow, much easier to use than tf