Autoencoding with K-Means

The MNIST dataset contains images of handwritten digits from 0 to 9. Using the machine learning K-Means algorithm to cluster the MNIST dataset achieves poor results. This experiment seeks to improve and measure the accuracy by using an autoencoder to massage the input data prior to K-Means. To measure the results a purity score will be generated and a confusion matrix will display the distribution of the clusters. The notebook is available on GitHub Generate…


Large Scale Augmented Reality

This is an experiment to test the state of augmented reality on the Apple iOS platform, by placing 3D models of historic structures in their original locations. I wanted to see how accurate the placement could be and how realistic they would appear. This post is intended to provide a little guidance to anyone starting out on an augmented reality project placing large objects using real world coordinates. The Workflow Figuring out the workflow was…


End of content

No more pages to load