# Classification Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/classification
> Markdown URL: https://aitinkerers.org/technologies/classification.md
> Technology record last updated: 2026-03-02T11:21:59Z
> Generated: 2026-10-24T15:04:19Z

Classification is a supervised machine learning technique: it predicts a discrete, categorical label for new data based on patterns learned from labeled training data.

Classification is a core supervised learning task where the model sorts input data into predefined classes (categories). The process requires a robust, labeled training dataset, which allows the algorithm to map input features to a specific output label (e.g., 'Spam' or 'Not Spam'). Key algorithms like Logistic Regression, Decision Trees, and K-Nearest Neighbors (KNN) execute this prediction. Real-world applications are critical: think financial models identifying a loan applicant as 'High Risk' or 'Low Risk,' or medical imaging systems classifying a tumor as 'Benign' or 'Malignant.' The goal is high accuracy across all classes, often measured by metrics like the F1 score and AUC (Area Under the Curve).

- Official technology site: https://www.datacamp.com/tutorial/classification-machine-learning
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Classifying Data with LLMs](https://amsterdam.aitinkerers.org/talks/rsvp_tkzXfpiXRgg)

- Event context: AI Tinkerers Amsterdam - September — 2024-09-25 — Amsterdam
- Public talk page: https://amsterdam.aitinkerers.org/talks/rsvp_tkzXfpiXRgg

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