![]() ![]() Each dimension you add, it becomes multiplicatively less likely that the point is not on the edge of at least one dimension, so in high dimensions, everything sits on the edge. Where else, if it is a square then the probability that they are in the middle means that they cannot be on the edge of either dimension so it is a little less likely that they are not on the edge. If you just have a single dimension where things are random, then they are spread out all over. There is this fascinating mathematical idea that the more dimensions you have, the more all of the points sit on the edge of that space. ![]() The curse of dimensionality is this idea that the more columns you have, it creates a space that is more and more empty. They are both largely meaningless and basically stupid and yet many people in the field not only know that but think the opposite so it is well worth explaining. Question: What about a curse of dimensionality? There are two concepts you often hear - curse of dimensionality and no free lunch theorem. Much appreciation to Jeremy and Rachel who gave me this opportunity to learn. These notes will continue to be updated and improved as I continue to review the course to “really” understand it. My personal notes from machine learning class. Make no mistake, however, the notes are still very informative. This first series includes notes for only 3 courses, while subsequent summaries (for the deep learning courses) include full course sets. ![]() The author of all of these notes, Hiromi Suenaga - which, in sum, are a great supplement review material for the course or a standalone resource in their own right - wanted to ensure that sufficient credit was given to course creators Jeremy Howard and Rachel Thomas in these summaries.īelow you will find links to the posts in this particular series, along with an excerpt from each post. Editor's note: This is one of a series of posts which act as a collection of a set of fantastic notes on the fast.ai machine learning and deep learning learning streams that are freely available online. ![]()
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