Supervised Learning — Teaching with Labels — Free AI & ML Tutorial
Learn Supervised Learning — Teaching with Labels in AI & ML with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
TL;DR: Learn Supervised Learning — Teaching with Labels in AI & ML with a free, beginner-friendly tutorial, examples and practice for Indian students on Syll…
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Supervised Learning — Teaching with Labels in AI & ML
Supervised Learning is the most common type of ML. "Supervised" means the training data is labelled — each example has an input AND a correct answer (label). The model learns the mapping from input to output.
Think of it like studying with an answer key. You practice problems and immediately know if you got it right or wrong. Over thousands of examples, you learn the pattern.
Two main types: Classification (output is a category, e.g., spam/not-spam, cat/dog, pass/fail) and Regression (output is a number, e.g., house price, temperature, marks).
Real examples: Email spam detection (classification), House price prediction (regression), Disease diagnosis from symptoms (classification), Stock price forecasting (regression), Handwriting recognition (classification).
Supervised Learning — Teaching with Labels — Syntax
# Supervised Learning structure: # Input (features) → Model → Output (label) # # Classification: output is a category # "Is this email spam?" → Yes/No # Regression: output is a number # "What will this house sell for?" → ₹45 lakhs
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