Synopsis
DESCRIPTIONData accumulated about customers, products, and website users can not only help interpret the past, it can help predict the future! Probabilistic programming is a programming paradigm in which code models are used to draw probabilistic inferences from data. By applying specialized algorithms, programs assign degrees of probability to conclusions and make it possible to forecast future events like sales trends, computer system failures, experimental outcomes, and other critical concerns.
Practical Probabilistic Programming explains how to use the PP paradigm to model application domains and express those probabilistic models in code. It shows how to use the Figaro language to build a spam filter and apply Bayesian and Markov networks to diagnose computer system data problems and recover digital images. Then it dives into the world of probabilistic inference, where algorithms help turn the extended prediction of social media usage into a science. The book covers functional-style programming for text analysis and using object-oriented models to predict social phenomena like the spread of tweets, and using open universe models to model real-life social media usage. It also teaches the principles of algorithms such as belief propagation and Markov chain Monte Carlo. The book closes out with modeling dynamic systems by using a product cycle as its main example and explains how probabilistic
KEY SELLING POINTS
Covers the basic rules of probabilistic inference
Illustrated with useful practical examples Build a wide variety of probabilistic modelsAUDIENCE
Code examples are written in Figaro. Some knowledge of Scala and a basic foundation in data science is helpful. No prior exposure to probabilistic programming is required.
ABOUT THE TECHNOLOGY
Probabilistic programming is a new discipline, and the tools and best practices are still emerging. Powerful new tools like the Figaro library built into Scala make probabilistic programming more practical in day-to-day work as a data scientist.
"synopsis" may belong to another edition of this title.
About the Author
Avi Pfeffer is the principal developer of the Figaro language for probabilistic programming. He graduated from Stanford, taught at Harvard, and is currently a principal scientist at Charles River Analytics."About this title" may belong to another edition of this title.
Search results for Practical Probabilistic Programming
Stock Image
Practical Probabilistic Programming
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Condition: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc. Seller Inventory # 00086064180
Stock Image
Practical Probabilistic Programming
Seller: ThriftBooks-Atlanta, AUSTELL, GA, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. Seller Inventory # G1617292338I4N00
Stock Image
Practical Probabilistic Programming
Seller: ThriftBooks-Dallas, Dallas, TX, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. Seller Inventory # G1617292338I4N00
Stock Image
Practical Probabilistic Programming
Published by
Manning (edition First Edition), 2016
ISBN 10: 1617292338
ISBN 13: 9781617292330
Used
Paperback
First Edition
Seller: BooksRun, Philadelphia, PA, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. First Edition. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Seller Inventory # 1617292338-11-1
Stock Image
Practical Probabilistic Programming
Seller: Wonder Book, Frederick, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: Good. Good condition. A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains. Seller Inventory # B14C-02400
Stock Image
Practical Probabilistic Programming
Seller: GoldBooks, Denver, CO, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: new. New Copy. Customer Service Guaranteed. Seller Inventory # 17O63_70_1617292338
Stock Image
Practical Probabilistic Programming Format: Paperback
Seller: INDOO, Avenel, NJ, U.S.A.
Seller rating 5 out of 5 stars
Condition: As New. Unread copy in mint condition. Seller Inventory # SS9781617292330
Stock Image
Practical Probabilistic Programming Format: Paperback
Seller: INDOO, Avenel, NJ, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Brand New. Seller Inventory # 9781617292330
Seller Image
Practical Probabilistic Programming
Published by
Manning Publications, US, 2016
ISBN 10: 1617292338
ISBN 13: 9781617292330
New
Paperback
Seller: Rarewaves USA, OSWEGO, IL, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: New. DESCRIPTION Data accumulated about customers, products, and website users can not only help interpret the past, it can help predict the future! Probabilistic programming is a programming paradigm in which code models are used to draw probabilistic inferences from data. By applying specialized algorithms, programs assign degrees of probability to conclusions and make it possible to forecast future events like sales trends, computer system failures, experimental outcomes, and other critical concerns. Practical Probabilistic Programming explains how to use the PP paradigm to model application domains and express those probabilistic models in code. It shows how to use the Figaro language to build a spam filter and apply Bayesian and Markov networks to diagnose computer system data problems and recover digital images. Then it dives into the world of probabilistic inference, where algorithms help turn the extended prediction of social media usage into a science. The book covers functional-style programming for text analysis and using object-oriented models to predict social phenomena like the spread of tweets, and using open universe models to model real-life social media usage. It also teaches the principles of algorithms such as belief propagation and Markov chain Monte Carlo. The book closes out with modeling dynamic systems by using a product cycle as its main example and explains how probabilistic KEY SELLING POINTS Covers the basic rules of probabilistic inference Illustrated with useful practical examples Build a wide variety of probabilistic models AUDIENCE Code examples are written in Figaro. Some knowledge of Scala and a basic foundation in data science is helpful. No prior exposure to probabilistic programming is required. ABOUT THE TECHNOLOGY Probabilistic programming is a new discipline, and the tools and best practices are still emerging. Powerful new tools like the Figaro library built into Scala make probabilistic programming more practical in day-to-day work as a data scientist. Seller Inventory # LU-9781617292330
Stock Image
Practi Probabil Programm
ISBN 10: 1617292338
ISBN 13: 9781617292330
New
Seller: Basi6 International, Irving, TX, U.S.A.
Seller rating 5 out of 5 stars
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Seller Inventory # ABEOCT25-316060