Have you ever wanted to use handy scikit-learn functionalities with your neural networks, but couldn’t because TensorFlow models are not compatible with the scikit-learn API? Now you can with one-line wrappers for TensorFlow/Keras models that enable you to use TensorFlow models within scikit-learn workflows with features like Pipeline, GridSearch and more.
All you have to do is swap out: keras.Model → KerasWrapperModel, or keras.Sequential → KerasSequentialWrapper. The wrapper objects have all the same methods of their keras counterparts, plus you can use them with tons of awesome scikit-learn methods!
All you have to do is swap out: keras.Model → KerasWrapperModel, or keras.Sequential → KerasSequentialWrapper. The wrapper objects have all the same methods of their keras counterparts, plus you can use them with tons of awesome scikit-learn methods!