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Mechanics of Materials
Author: Roy R. Craig, Jr.
language: en
Publisher: John Wiley & Sons
Release Date: 2020-08-04
The fourth edition of Mechanics of Materials is an in-depth yet accessible introduction to the behavior of solid materials under various stresses and strains. Emphasizing the three key concepts of deformable-body mechanics—equilibrium, material behavior, and geometry of deformation—this popular textbook covers the fundamental concepts of the subject while helping students strengthen their problem-solving skills. Throughout the text, students are taught to apply an effective four-step methodology to solve numerous example problems and understand the underlying principles of each application. Focusing primarily on the behavior of solids under static-loading conditions, the text thoroughly prepares students for subsequent courses in solids and structures involving more complex engineering analyses and Computer-Aided Engineering (CAE). The text provides ample, fully solved practice problems, real-world engineering examples, the equations that correspond to each concept, chapter summaries, procedure lists, illustrations, flow charts, diagrams, and more. This updated edition includes new Python computer code examples, problems, and homework assignments that require only basic programming knowledge.
Python Guide for Introductory Econometrics for Finance
Author: Chris Brooks
language: en
Publisher: Cambridge University Press
Release Date: 2019-03-28
This free software guide for Python with freely downloadable datasets brings the econometric techniques to life, showing readers how to implement the approaches presented in Introductory Econometrics for Finance using this highly popular software package. Designed to be used alongside the main textbook, the guide will give readers the confidence and skills to estimate and interpret their own models while the textbook will ensure that they have a thorough understanding of the conceptual underpinnings.
Introduction to the Tools of Scientific Computing
The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike standard approaches, it does not focus on any specific language, but aims to explain the underlying ideas. Typically, new concepts are first introduced in the particularly user-friendly Python language and then transferred and extended in various programming environments from C/C++, Julia and MATLAB to Maple and Mathematica. This includes various approaches to distributed computing. By examining and comparing different languages, the book is also helpful for mathematicians and practitioners in deciding which programming language to use for which purposes. At a more advanced level, special tools for the automated solution of partial differential equations using the finite element method are discussed. On a more experimental level, the basic methods of scientific machine learning in artificial neural networks are explained and illustrated.