Description: Probabilistic Machine Learning for Civil Engineers by James-A. Goulet Estimated delivery 3-12 business days Format Paperback Condition Brand New Description An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises. Publisher Description An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises.This book introduces probabilistic machine learning concepts to civil engineering students and professionals, presenting key approaches and techniques in a way that is accessible to readers without a specialized background in statistics or computer science. It presents different methods clearly and directly, through step-by-step examples, illustrations, and exercises. Having mastered the material, readers will be able to understand the more advanced machine learning literature from which this book draws.The book presents key approaches in the three subfields of probabilistic machine learning- supervised learning, unsupervised learning, and reinforcement learning. It first covers the background knowledge required to understand machine learning, including linear algebra and probability theory. It goes on to present Bayesian estimation, which is behind the formulation of both supervised and unsupervised learning methods, and Markov chain Monte Carlo methods, which enable Bayesian estimation in certain complex cases. The book then covers approaches associated with supervised learning, including regression methods and classification methods, and notions associated with unsupervised learning, including clustering, dimensionality reduction, Bayesian networks, state-space models, and model calibration. Finally, the book introduces fundamental concepts of rational decisions in uncertain contexts and rational decision-making in uncertain and sequential contexts. Building on this, the book describes the basics of reinforcement learning, whereby a virtual agent learns how to make optimal decisions through trial and error while interacting with its environment. Author Biography James-A. Goulet is Associate Professor of Civil Engineering at Polytechnique Montreal. Details ISBN 0262538709 ISBN-13 9780262538701 Title Probabilistic Machine Learning for Civil Engineers Author James-A. Goulet Format Paperback Year 2020 Pages 304 Publisher MIT Press Ltd GE_Item_ID:141686336; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
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ISBN-13: 9780262538701
Book Title: Probabilistic Machine Learning for Civil Engineers
Number of Pages: 304 Pages
Publication Name: Probabilistic Machine Learning for Civil Engineers
Language: English
Publisher: MIT Press
Item Height: 0.5 in
Publication Year: 2020
Subject: Probability & Statistics / General, Intelligence (Ai) & Semantics, Civil / General, Computer Engineering
Type: Textbook
Item Weight: 26.3 Oz
Subject Area: Mathematics, Computers, Technology & Engineering
Author: James-A. Goulet
Item Length: 10 in
Item Width: 8 in
Format: Trade Paperback
