Description: Machine Learning in Geomechanics 2 : Data-driven Modeling, Bayesian Inference, Physics- and Thermodynamics-based Artificial Neural Networks and Reinfor, Hardcover by Stefanou, Ioannis (EDT); Darve, Félix (EDT), ISBN 1789451930, ISBN-13 9781789451931, Like New Used, Free shipping in the US Machine learning has led to incredible achievements in many different fields of science and technology. These varied methods of machine learning all offer powerful new tools to scientists and engineers and open new paths in geomechanics. The two volumes of Machine Learning in Geomechanics aim to demystify machine learning. They present the main methods and provide examples of its applications in mechanics and geomechanics. Most of the chapters provide a pedagogical introduction to the most important methods of machine learning and uncover the fundamental notions underlying them. Building from the simplest to the most sophisticated methods of machine learning, ths give several hands-on examples of coding to assist readers in understanding both the methods and their potential and identifying possible pitfalls.
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End Time: 2024-11-28T21:32:08.000Z
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Book Title: Machine Learning in Geomechanics 2 : Data-driven Modeling, Bayesi
Number of Pages: 304 Pages
Language: English
Publication Name: Machine Learning in Geomechanics 2 : Data-Driven Modeling, Bayesian Inference, Physics- and Thermodynamics-Based Artificial Neural Networks and Reinforcement Learning
Publisher: Wiley & Sons, Incorporated, John
Publication Year: 2024
Subject: Physics / Geophysics
Item Weight: 23.5 Oz
Type: Textbook
Author: Félix Darve
Subject Area: Science
Series: Iste Consignment Ser.
Format: Hardcover
