Description

Supervised Learning is a machine learning approach where an algorithm learns to map input data to output labels based on example input-output pairs. The algorithm is trained on a labeled dataset, where each example in the training data is paired with the correct output. The goal is for the algorithm to learn a general rule that maps inputs to outputs, which can then be used to make predictions on new, unseen data.

Examples

• 📧 Email spam detection
• 🖼️ Image classification
• ✍️ Handwriting recognition
• 🏠 Predicting house prices

Applications