Supervised Learning
Machine learning approach where the model learns from labeled training data (inputs with known outputs).
In more detail
In supervised learning, each training example has associated labels or target values. The model learns to map inputs to outputs by minimizing prediction error. Common applications include classification (predicting categories) and regression (predicting continuous values). Examples include email spam detection and house price prediction.
Examples
- Email spam classification
- Medical diagnosis from imaging
- Credit default prediction
- Handwritten digit recognition (MNIST)
Related terms
Ready to Build Production AI Systems?
Join a small cohort learning directly from an engineer who's shipped AI at Atlassian and PhonePe scale.
20 weeks · Weekend live classes · 1:1 mentorship · 20+ projects.
20 Weeks
Live Weekend Classes
< 30 Seats
Small Batch
Next Soon
Get priority access
7-Day
Money-Back Guarantee
Taught by Debasish Maji · Senior AI Engineer · Ex-Atlassian (Rovo Agent) · Ex-PhonePe (550M+ users)
Get notified when the next batch opens + free AI resources