Practical Probabilistic Programming

Practical Probabilistic Programming Avi Pfeffer
The data you accumulate about your customers, products, and website users can not only help you interpret your past, it can help you predict your future! Probabilistic program-ming uses code to draw probabilistic inferences from data. By applying specialized algorithms, your programs assign degrees of probability to conclusions. This means you can forecast future events like sales trends, computer system failures, experimental outcomes, and many other critical concerns. Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In this book, you’ll immediately work on practical examples like building a spam filter, diagnosing computer system data problems, and recovering digital images. You’ll discover probabilistic inference, where algorithms help make extended predictions about issues like social media usage. Along the way, you’ll learn to use functional-style programming for text analysis, object-oriented models to predict social phenomena like the spread of tweets, and open universe models to gauge real-life social media usage. The book also has chapters on how probabilistic models can help in decision making and modeling of dynamic systems.  What’s Inside
• Introduction to probabilistic modeling
• Writing probabilistic programs in Figaro
• Building Bayesian networks
• Predicting product lifecycles
• Decision-making algorithms
This book assumes no prior exposure to probabilistic programming. Knowledge of Scala is helpful. Avi Pfeffer is the principal developer of the Figaro language for probabilistic programming. Categories:
Computers – Algorithms and Data Structures
Year:
2016
Edition:
1
Publisher:
Manning Publications
Language:
english
Pages:
427 / 458
ISBN 10:
1617290653
ISBN 13:
9781617292231
File:
49 MB