From the course: Data Science for Java Developers
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Supervised vs. unsupervised learning - Java Tutorial
From the course: Data Science for Java Developers
Supervised vs. unsupervised learning
- [Instructor] Okay, the next thing we're going to talk about is the fact that there are actually two main categories that the models we build are going to fall into. And it's usually pretty important to have some idea of this distinction before we actually get into building our models. Because this distinction will make quite a difference in the approach that we ended up taking in the end. So the two categories that these models generally fall into are models that are trained using supervised learning and models that are trained using unsupervised learning. So let's take a look at what both of these means and just kind of what it's going to mean for the models we build. Unsupervised learning aims to identify natural groupings that occur in our data sets without actually having any preconceived notions of what those groups might be. So an example of a question we might be asking ourselves that would be solved with…
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