In Python using Tensorflow design a Feed Forward neural network to predict a regression problem with 40 features. To stick to the style of a Feed Forward architecture we continue with 40 neurons down our Dense or fully connected layers. Although adding in more Dense layers will help at first the comes a point we more Dense layers won't help with the problem any further.
A good way to look at this is your dataset has only a certain number of higher-level features discoverable by the network and adding more layers when there are no more higher features to find won't add value. How many layers? Experimentation is the solution to finding the perfect amount for your data set.
Follow Data Science Teacher Brandyn
dataGroups:
