In this project I am creating a grid search cross validation with Keras and scikit-learn for deep learning. My goal is to automate the hyperparameter tuning and maximise the accuracy with a script that could be applicable to multiple datasets with only little adjustment.
I used the pre-processing ideas from Udacity and got also inspired by this post: https://machinelearningmastery.com/grid-search-hyperparameters-deep-learning-models-python-keras/
I am very happy to take constructive criticism, advice, and of course ... praise. :)