| Description |
1 online resource : color illustrations |
| Note |
Includes index. |
| 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. |
| Summary |
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. -- Edited summary from book. |
| Subject |
Stochastic programming.
|
|
Probabilities -- Data processing.
|
|
Operations Research. |
|
Civil & Environmental Engineering. |
|
Engineering & Applied Sciences. |
|
Programmation stochastique. |
|
Probabilités -- Informatique. |
|
Probabilities -- Data processing |
|
Stochastic programming |
| Other Form: |
Print version: Pfeffer, Avi. Practical probabilistic programming. Shelter Island, NY : Manning Publications, Co., [2016] (DLC) 2016301895 |
| ISBN |
1638352372 (electronic bk.) |
|
9781638352372 (electronic bk.) |
|
More Resources