Where is the “learning” in machine learning? The problem with machine learning algorithms is that they yield a final solution without giving you a sense of the learning process. So I’ve implemented an interactive version of a perceptron learning algorithm. To run the algorithm I need lenearly separable data – hence the posts from the previous weeks. Now I can use that as the basis for visualising the machine learning steps.
The video below illustrates how I have used table properties such as row selections, marker shapes and colour associations to help interactively visualise the behaviour of a machine learning algorithm. The algorithm is based on a perceptron.