Simple syntax and mainly the applications of CNN models in the domain of deep learning Review collected by and hosted on G2.com.
Lack of online resources mainly in terms of Transformer models and NLP. Review collected by and hosted on G2.com.
The level of control to write algorithms/networks from scratch is relatively high. It also is faster in executing the networks and comes with an optional keras frontend to make it easier for developer to develop networks. Review collected by and hosted on G2.com.
Without keras as frontend, using raw theano has a high learning curve. Review collected by and hosted on G2.com.
Theano is a Python library and is good for making algorithms from scratch.
I used standard algorithms and wrote Pylearn2 plugins as Theano expressions, and Theano optimized and stabilize the expressions. It includes all things needed for multilayer perceptron/RBM/Stacked Denoting Autoencoder/ConvNets. Review collected by and hosted on G2.com.
Documentation is a little tough to understand. Review collected by and hosted on G2.com.