This brief post is exploring overfitting neural networks. It comes from reading the paper: Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes

Here we will find some data to see what the state of renewable energy production is within Europe. The data is collected from: https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show

In this post I will attempt to go over the steps between a simple linear regression towards a non-linear probabilistic model built with a neural network.

Here we look at fitting a normal distribution to some data using Tensorflow Probability.

We compare the performance of adding a batch normalisation layer to a convolution neural network (CNN). For this we use the results from a previous post on creating a CNN for fashion MNIST data: