From the course: Machine Learning with Scikit-Learn

What is supervised learning? - scikit-learn Tutorial

From the course: Machine Learning with Scikit-Learn

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What is supervised learning?

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- [Instructor] The most common form of machine learning is supervised learning. In Scikit-Learn, a supervised learning algorithm learns a relationship between your features matrix and your target factor. A feature is a measurable property. A target is typically what you want to make predictions for. Once a model learns a relationship between a features matrix and a target factor, it can make predictions for unseen or future data. Supervised learning can generally be thought of to solve two different types of tasks. The first is when you try to predict a continuous value. This is considered a regression problem. This means that your target factor contains continuous qualities like home prices. The second is when you're trying to predict a categorical value. This is considered a classification problem. This means that your target factor contains categorical values like different flower species. So that's it. Supervised learning is when an algorithm learns from a features matrix and target factor to make predictions.

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