Probably programming in practice

Probabilistic programming is a new way to create probabilistic models that allow you to predict or withdraw new facts that are not in the results of observations. This allows, for example, to predict such future events such as sales trends, refusal of computing systems, exodus experiments and much more.
The book is an introduction to probabilistic programming for practitioners. The author almost immediately proceeds to practical examples: building a spam filter, error diagnostics in a computing system, to restore digital images. You will get acquainted with a probabilistic conclusion where algorithms help predict, for example, the use of social networks. Along the way, you will find out about the use of functional programming style for analyzing texts, object-oriented models - to predict the spread of tweets, and models with an open universe - to measure phenomena in the social network. The book also has chapters on how probabilistic models help in making decisions and modeling dynamic systems.
you collected data about customers, products and users of the site can assist not only in the interpretation of the past, but also in the prediction of the future!
Summary:
- Introduction to probabilistic modeling,
- Writing probabilistic programs on Figaro,
- Building Bayesian networks,
- Forecasting product life cycle,
- decision-making algorithms