Book Name: Practical Probabilistic Programming
Author: Avi Pfeffer
Publisher: Manning Publications
File size: 6.69 MB
File format: PDF
Practical Probabilistic Programming Pdf Book Description:
Data gathered regarding customers, products, and site users can’t just help translate the past, it may help forecast the future! Probabilistic programming is a programming paradigm where code versions are utilized to draw probabilistic inferences from information. By applying specialized calculations, programs assign levels of probability to decisions and make it feasible to predict future events such as earnings trends, computer system failures, experimental results, along with other crucial issues. Practical Probabilistic Programming describes how to utilize the PP paradigm to simulate application domain names and express these probabilistic versions in code. It reveals how to utilize the Figaro terminology to construct a spam filter and then employ Bayesian and Markov networks to diagnose pc system info issues and retrieve digital pictures.
Then it drops into the sphere of probabilistic inference, where calculations help turn the elongated forecast of social networking use to some science. The publication covers functional-style programming for text analysis and utilizing object-oriented models to forecast social phenomena such as the spread of tweets, and utilizing open world models to simulate real-life social networking use. The book ends up with simulating dynamic systems using a product cycle because its principal example and clarifies how probabilistic models will help in the decision-making procedure for an advertising campaign.
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