Supervised Learning

A type of machine learning where the algorithm learns from labeled training data.

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

💳 Credit risk assessment

🩺 Medical diagnosis

🔮 Customer churn prediction

📝 Optical character recognition

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