ML 3: Supervised Learning with Examples

Supervised learning is a type of machine learning where the model is trained on labeled data, meaning that each training example is paired with an output label. Examples of supervised learning algorithms include:

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• Linear Regression: Used for predicting continuous values, such as house prices based on features like size and location.

• Logistic Regression: Used for binary classification tasks, such as determining whether an email is spam or not.

• Decision Trees: A model that makes decisions based on questions about the features, useful for both classification and regression tasks.

• Support Vector Machines (SVM): Effective in high-dimensional spaces for classification problems.

• Neural Networks: Particularly powerful for complex tasks such as image and speech recognition.