Machine Learning Methods in Geotechnical Engineering

Explore the applications of Machine Learning in geotechnical engineering through this informative webinar hosted by Prof Majid Nazem of RMIT University, Melbourne, Australia. Discover how to generate training sets using OPTUM G2 and learn about the applicability of various Machine Learning techniques in geomechanics problems such as slope stability, load bearing capacity of piles, dynamic penetration, and predicting soil properties. Gain insights into the advantages of AI models over statistical models in predicting soil behavior, particularly in complex problems with highly nonlinear relationships among influential parameters. Understand the principles behind Machine Learning approaches in AI and their potential to revolutionize geotechnical engineering practices.

Machine Learning Methods in Geotechnical Engineering