Browse Subject Headings
Machine Learning in Geomechanics 2 : Data-Driven Modeling, Bayesian Inference, Physics- and Thermodynamics-Based Artificial Neural Networks and Reinforcement Learning
Machine Learning in Geomechanics 2 : Data-Driven Modeling, Bayesian Inference, Physics- and Thermodynamics-Based Artificial Neural Networks and Reinforcement Learning
Click to enlarge
ISBN No.: 9781789451931
Pages: 304
Year: 202411
Format: Trade Cloth (Hard Cover)
Price: $ 227.70
Dispatch delay: Dispatched between 7 to 15 days
Status: Available

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, the books give several hands-on examples of coding to assist readers in understanding both the methods and their potential and identifying possible pitfalls.


To be able to view the table of contents for this publication then please subscribe by clicking the button below...
To be able to view the full description for this publication then please subscribe by clicking the button below...
Browse Subject Headings