Practical probabilistic programming
Introducing the working programmer to probabilistic programming (PP), this book will teach you how to use the PP paradigm to model application domains and then express those probabilistic models in code. --
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| Format: | eBook |
| Language: | English |
| Published: |
Shelter Island, NY
Manning Publications Co.
2016
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| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- Probabilistic programming in a nutshell
- A quick Figaro tutorial
- Creating a probabilistic programming application
- Probabilistic models and probabilistic programs
- Modeling dependencies with Bayesian and Markov networks
- Using Scale and Figaro collections to build up models
- Object-oriented probabilistic modeling
- Modeling dynamic systems
- The three rules of probabilistic inference
- Factored inference algorithms
- Sampling algorithms
- Solving other inference tasks
- Dynamic reasoning and parameter learning