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Probabilistic programming (PP)
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A programming paradigm that unifies probabilistic modeling with general-purpose programming for easier specification and inference.
Technical Definition
A programming paradigm that unifies probabilistic modeling with general-purpose programming for easier specification and inference.
How it works
Probabilistic programming (PP) allows developers to build probabilistic models using programming languages. It automates the complex task of performing inference on these models, making it easier to handle uncertainty and build sophisticated AI systems for decision-making.
Related Concepts
- Inference — Using a trained model to make predictions on new data — the deployment phase of machine learning.
- Declarative programming — A programming paradigm that expresses the logic of a computation without explicitly describing its control flow.