Classification vs Regression

Classification:

Classification algorithms attempt to predict a discrete class label. For example, a problem where you are trying to build a model(or algorithm) to interpret whether an image is a dog or a cat would be a classification problem.

Some Common Classification Machine Learning Algorithms/models:
- K Nearest Neighbors
- Support Vector Machine
- Logistic Regression
- Random Forest Classifier
- Decision Trees
- Neural Networks

Regression:

On the other hand, regression algorithms attempt to predict a continuous quantity. An example of a regression problem would be when you're trying to predict the prices of homes, where the prediction could be an integer, fraction, or decimal number.

Some Common Regression Machine Learning Algorithms/models:
- Linear Regressor
- Polynomial Regressor
- Lasso Regressor
- Ridge Regressor
- Elastic Net Regressor
- Support Vector Regressor
- Regression Trees
- Neural Networks

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Overfitting vs Underfitting

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