Machine Learning From Scratch

The purpose of this project is not to produce as optimized and computationally efficient algorithms as possible but rather to present the inner workings of them in a transparent and accessible way. Figure: Training progress of a regularized polynomial regression model fitting temperature data measured in Linköping, Sweden 2016. Figure: Shows how the network gets better during training at reconstructing the digit 2 in the MNIST dataset. Figure: Classification of the digit dataset by a neural network which has been evolutionary evolved.