Jul 4, 2013 — Markov Decision Processes — To talk about Markov Decision Processes we venture into Reinforcement Learning, which is a kind of learning that is based on optimization using a reward function.  For example, let’s say that we are training a robot to navigate a space without... Read more

Jul 3, 2013 — Principal Component Analysis (PCA) — What is Principal Component Analysis? **Principal Components Analysis (PCA) **is an algorithm most commonly used for dimensionality reduction that finds a one dimensional subspace that best approximates a dataset.  When you have data with many (possibly correlated) features, PCA finds... Read more

Jul 2, 2013 — Meyer Watershed Segmentation — Imagine that the pixel intensities of an image form a landscape, with lower values (closer to zero, corresponding to black) forming valleys, and higher values (closer to 1, white) forming mountains.  Our image isn’t an image, in fact, it is... Read more

Jul 2, 2013 — Median Filtering — Median filtering is another filtering technique similar to convolution in that we define a small window ( an nxn square smaller than our image) to move across it, and based on the pixels that fall within that window, we define... Read more