What is supervised learning?
Supervised learning is teaching by example.
How It Works:
Supervised learning trains models on labeled datasets, adjusting parameters to minimize the error between predictions and known outputs.
Key Benefits:
- Predictable outcomes: Clear performance metrics.
- Broad applicability: Classification, regression, and more.
- Mature tooling: Wide support in ML libraries.
Real-World Use Cases:
- Spam detection: Emails labeled ?spam? or ?not spam.?
- Price prediction: Predict home values from historical sales.
FAQs
How obtain labels?
When use supervised vs. unsupervised?
.png)
.svg)
