Can anyone explain about regression in machine learning?

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Regression in Machine Learning is a type of supervised learning that involves predicting a continuous quantity for the new examples based on observed patterns from the previous data. In simple words, if the target variable is continuous then it is a regression problem.

I have listed a few most used regression algorithms in machine learning:

- Linear regression
- Lasso regression
- Ridge regression
- Decision trees
- Random forest regression
- K-Nearest neighbors

Examples: Predicting the prices of houses based on the attributes of a house like the number of rooms, the size of a house, etc.

If you are interested in Machine learning, I suggest this Machine learning course by Intellipaat.

You can watch this video to know about regression in machine learning: