From the course: Data Science Foundations: Fundamentals
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Classifying
From the course: Data Science Foundations: Fundamentals
Classifying
- [Instructor] So maybe you've got a dog, and maybe your dog does cute things like sticking its nose in your camera. Now, my dog's too short for that, but you take a picture or a video to save the moment. But one interesting consequence of that process is that now your phone's photo program is going to start analyzing the photo to determine what it's a photo of. That way, you can search for it later by typing dog, without ever having had to tell the program that's what it is. And that's the result of a machine learning algorithm taking the data to analyze the photos and classify it as a dog, a cat, a child, and add those labels to the data. In fact, classifying is one of the most important tasks that data science algorithms perform, and they do it on all kinds of data. The general idea of automated classification is pretty simple to describe. Locate the case in a K-dimensional space, where K is the number of variables…
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