Geo.Engineerings

Sayavur I. Bakhtiyarov ... 125 pages - Publisher: Morgan&Claypool; (October, 2017) ... Language: English - ISBN-10: 168173611X - ISBN-13: 978-1681736112.

Engineering mechanics is one of the fundamental branches of science that is important in the education of professional engineers of any major. Most of the basic engineering courses, such as mechanics of materials, fluid and gas mechanics, machine design, mechatronics, acoustics, vibrations, etc. are based on engineering mechanics courses. In order to absorb the materials of engineering mechanics, it is not enough to consume just theoretical laws and theorems—a student also must develop an ability to solve practical problems. Therefore, it is necessary to solve many problems independently. This book is a part of a four-book series designed to supplement the engineering mechanics courses. This series instructs and applies the principles required to solve practical engineering problems in the following branches of mechanics: statics, kinematics, dynamics, and advanced kinetics. Each book contains between 6 and 8 topics on its specific branch and each topic features 30 problems to be assigned as homework, tests, and/or midterm/final exams with the consent of the instructor. A solution of one similar sample problem from each topic is provided. This first book contains seven topics of statics, the branch of mechanics concerned with the analysis of forces acting on construction systems without an acceleration (a state of the static equilibrium). The book targets the undergraduate students of the sophomore/junior level majoring in science and engineering.

Terrence J. Sejnowski ... 354 pages - Publisher: MIT Press; (2018) ... Language: English - ISBN-10: 9780262038034 - ISBN-13: 978-0262038034.

How deep learning -from Google Translate to driverless cars to personal cognitive assistants- is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.

Oliver M. O'Reilly ... 540 pages - Publisher: Cambridge Univ. Press; 2nd edition (March, 2020) ... Language: English - ISBN-10: 1108494218 - ISBN-13: 978-1108494212.

Suitable for both senior-level and first-year graduate courses, this fully revised edition provides a unique and systematic treatment of engineering dynamics that covers Newton-Euler and Lagrangian approaches. New to this edition are: two completely revised chapters on the constraints on, and potential energies for, rigid bodies, and the dynamics of systems of particles and rigid bodies; clearer discussion on coordinate singularities and their relation to mass matrices and configuration manifolds; additional discussion of contravariant basis vectors and dual Euler basis vectors, as well as related works in robotics; improved coverage of navigation equations; inclusion of a 350-page solutions manual for instructors, available online; a fully updated reference list. Numerous structured examples, discussion of various applications, and exercises covering a wide range of topics are included throughout, and source code for exercises, and simulations of systems are available online.

Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong ... 398 pages - Publisher: Cambridge Univ. Press; (April, 2020) ... Language: English - AmazonSIN: B083M7DBP6.

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Donald P. Coduto, William A. Kitch, Man-Chu Ronald Yeung ... 984 pages - Publisher: Pearson; 3rd edition (January, 2015) ... Language: English - ISBN-10: 0133411893 - ISBN-13: 978-0133411898.

Jacob Bear ... 592 pages - Publisher: Dover Publications; (January, 2007) ... Language: English - ISBN-10: 0486453553 - ISBN-13: 978-0486453552.

This text explores the laws and equations that govern the flow and storage of groundwater in aquifers. It provides groundwater hydrologists, as well as engineers and planners who deal with the development and management of groundwater resources, with all the necessary tools to forecast the behavior of a regional aquifer system. Following an introduction to the role and management of groundwater in water resource systems, the text examines groundwater balance and motion, mathematical statements of the groundwater forecasting problem, flow in the unsaturated zone, and groundwater quality problems. Additional topics include hydraulics of pumping and recharging wells, fresh and salt water interface in coastal aquifers, modeling of aquifer systems, identification of aquifer parameters, and the use of linear programming in aquifer management. Helpful appendixes and a set of problems corresponding to selected chapters conclude the text.