This is the first in a multi-part examination of the theory and implementation of Markov probability models in JavaScript. In this post, we’ll examine the simplest type of Markov Model, the Observable Markov Chain.
Ideas have a funny way of spreading. Sometimes a concept that has become ubiquitous in a particular field of study can take years to be widely understood in another field that could have equal use for it.
Variations of Markov Models have found many uses in computer programming recently, from stock trading algorithms to speech recognition systems. However, there is a dearth of solid explanation for client-side JavaScript implementation. I’d imagine this has to do with the fact that JavaScript in web browsers was historically too slow and lacked the low-level access to audio/video input for many of the common uses of these probability models to be implemented. Fortunately, with massive cross-browser performance improvements, and new multimedia API’s such as WebRTC in the pipeline, these limitations are becoming problems of the past. …Read more: Markov Models in JavaScript Part I: An Observable Markov Chain