Description: Probabilistic Graphical Models: Principles and Techniques [Adaptive Computation ISBN or UPC: 9780262013192 Book Condition: Used - Good Description: May have some shelf-wear due to normal use. Your purchase funds free job training and education in the greater Seattle area. Thank you for supporting Goodwill's nonprofit mission! Our customer's satisfaction is our top priority. In the event you experience any problems with your order, please contact us prior to leaving a negative or neutral feedback and we'll be sure to offer a speedy resolution to any issues that may arise. Stock photos may not be available on the eBay catalog for all listings. If you purchase an item that doesn't include a photo and it's not what you were expecting, please contact us, and we will take care of your concerns. SEATTLE GOODWILL'S MISSION: Goodwill® provides quality, effective employment training and basic education to individuals experiencing significant barriers to economic opportunity. Donations of quality reusable items from the public are sold in our retail stores and online. Net proceeds from the sale of these goods and financial donations from the community make it possible for us to operate our free job training programs. Your donations and purchases help support these important programs and make the community a better place for all of us.
Price: 34.29 USD
Location: Seattle, Washington
End Time: 2025-01-05T20:04:27.000Z
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Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
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Number of Pages: 1270 Pages
Language: English
Publication Name: Probabilistic Graphical Models : Principles and Techniques
Publisher: MIT Press
Publication Year: 2009
Subject: Programming / Algorithms, Intelligence (Ai) & Semantics, Probability & Statistics / Bayesian Analysis
Item Height: 2 in
Item Weight: 78 Oz
Type: Textbook
Subject Area: Mathematics, Computers
Item Length: 9.4 in
Author: Nir Friedman, Daphne Koller
Item Width: 8.3 in
Series: Adaptive Computation and Machine Learning Ser.
Format: Hardcover
