Train a simple Multilayer Perceptron using TensorFlow 2

Train a simple Multilayer Perceptron using TensorFlow 2 for a binary classification

This workflow shows how to train a simple multilayer perceptron for classification. It is demonstrated how the "DL Python Network Creator" can be used to create a simple neural network using the tf.keras API and how the "DL Python Network Learner" can be used to train the created network on data.
Please note this example should demonstrate how to set up the deep learning environment with Tensor Flow 2 and provide a working simple example.

External resources

• KNIME Deep Learning Integration Installation Guide
• adapted from: Train a simple Multilayer Perceptron using TensorFlow 2
• TensorFlow 2 Tutorial: Get Started in Deep Learning With tf.keras
• Codeless Deep Learning with KNIME
• please download the complete DeepLearning (Keras, Tensorflow, H2O.ai) Workflow group
• (official) KNIME Python Integration Guide
• Meta Collection about KNIME and Python
• (official) KNIME Deep Learning Integration Installation Guide
• Medium: KNIME and Python — Setting up and managing Conda environments
• compact KNIME forum - "KNIME - Python and Deep Learning"
• KNIME Hub - Train a simple Multilayer Perceptron using TensorFlow 2
• (knime forum hint) Tensorflow and python-flatbuffers<2.0