a thin scikit-learn style wrapper for tensorflow framework
The wrapper takes care of training (fit()) and prediction(predict()) infrastructure.
What is left to do is to specify the network topology in _create_network() method and
loss function in _create_loss() method.
There are two subclasses of the tflearn class
which come with ready to use _create_loss() method:
rtflearnfor regressionctflearnfor classification (in progress)
tf_lasso.py: Lasso regression, a simplest example
tf_factorization_machine.ipynb : Factorization machines
gan_dense.py : Generative adversarial network with dense perceptron layers