KNIME Tips and Tricks

Throughout the book, we covered many case studies, implemented using KNIME Analytics Platform. In the KNIME Hub space of this book, you can find these workflows and you can use them as a starting point for your deep learning projects: https://hub.knime.com/kathrin/spaces/Codeless%20Deep%20Learning%20with%20KNIME/latest/. In this last section, we want to share some tips and tricks to work with deep learning in KNIME Analytics Platform.

Let's start with data shuffling for training.

Shuffling Data during Training

When training neural networks, for faster convergence of the training process and to avoid overfitting, it is recommended to shuffle the training data before each epoch.

To do that, make sure you activate the Shuffle training data before each epoch checkbox in the Advanced tab in the configuration window of the Keras Network Learner node.

Using Batch Normalization

Batch normalization is a technique that standardizes the data in each...