This case study is part of IBM's Introduction to Deep Learning & Neural Networks with Keras Course. It consists of building a regression model using the Keras library to model data about concrete's compressive strength. The goal is to experiment with building a neural network by increasing the number of training epochs and changing number of hidden layers to observe how changing these parameters impacts the performance of the model.
A binder with an interactive Jupyter notebook in Python3 can be found here by launching JupyterLab
