This post is a collection of three tiny demos I wrote while taking Daniel Shiffman’s Intelligence and Learning course. The three apps demonstrate the uses of some machine intelligence techniques from rudimental algorithms to convolutional neural network.
Visualizing the K-Nearest Neighbor algorithm. I ran a KD-Tree accelerated KNN search on constantly changing data set to demonstrate its realtime ability.
This is an app that runs grid based A* pathfinding algorithm on arbitray city street maps. The grid connectivity information is obtained from bitmaps.
This is an interactive app that runs the MIT Places365 pre-trained CNN model for scene recognition. It uses the C++ API of Caffe deep learning framework.