Geo.Engineerings

This book provides a snapshot of the research activities of the Institute of Geotechnical Engineering, University of Natural Resources and Life Sciences in Vienna, Austria. The topics are broad ranged including: · Centrifuge model testing · Constitutive model · Granular physics · Numerical simulation · Soil bioengineering. The topics reflect our geotechnical research in a changing world. Traditional topics in foundation engineering are fading out and new topics are emerging. The European Commission is gratefully acknowledged for funding the following projects within its program FP7 and Horizon2020: MUMOLADE (Multiscale modelling of landslide and debris flow), REVENUES (Reinforced Vegetation Numerical Evaluation of Slopes) and GEORAMP (Geohazards - Risk Assessment, Mitigation and Prevention).

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming. What You Will Learn: Perform data science and analytics using statistics and the R programming language + Visualize and explore data, including working with large data sets found in big data + Build an R package + Test and check your code + Practice version control + Profile and optimize your code.