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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 https://github.com/MichaelSchlachter/clustering/blob/master/mnist_encoder_kmeans.ipynb Generate…

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…