Geo.Engineerings

Jalil Villalobos Alva ... 448 pages - Language: English - Publisher: Apress; 2nd edition (July, 2024).

Enhance your data science programming and analysis with the Wolfram programming language and Mathematica, an applied mathematical tools suite. This second edition introduces the latest LLM Wolfram capabilities, delves into the exploration of data types in Mathematica, covers key programming concepts, and includes code performance and debugging techniques for code optimization.

You’ll gain a deeper understanding of data science from a theoretical and practical perspective using Mathematica and the Wolfram Language. Learning this language makes your data science code better because it is very intuitive and comes with pre-existing functions that can provide a welcoming experience for those who use other programming languages. Existing topics have been reorganized for better context and to accommodate the introduction of Notebook styles. The book also incorporates new functionalities in code versions 13 and 14 for imported and exported data.

You’ll see how to use Mathematica, where data management and mathematical computations are needed. Along the way, you’ll appreciate how Mathematica provides an entirely integrated platform: its symbolic and numerical calculation result in a mized syntax, allowing it to carry out various processes without superfluous lines of code. You’ll learn to use its notebooks as a standard format, which also serves to create detailed reports of the processes carried out.

What You Will Learn: Create datasets, work with data frames, and create tables + Import, export, analyze, and visualize data + Work with the Wolfram data repository + Build reports on the analysis + Use Mathematica for machine learning, with different algorithms, including linear, multiple, and logistic regression; decision trees; and data clustering.

Charu C. Aggarwal ... 553 pages - Language: English - Publisher: Springer; 2nd edition (June, 2023).

Neural networks were developed to simulate the human nervous system for Machine Learning tasks by treating the computational units in a learning model in a manner similar to human neurons. The grand vision of neural networks is to create artificial intelligence by building machines whose architecture simulates the computations in the human nervous system. Although the biological model of neural networks is an exciting one and evokes comparisons with science fiction, neural networks have a much simpler and mundane mathematical basis than a complex biological system. The neural network abstraction can be viewed as a modular approach of enabling learning algorithms that are based on continuous optimization on a computational graph of mathematical dependencies between the input and output. These ideas are strikingly similar to classical optimization methods in control theory, which historically preceded the development of neural network algorithms.

For courses in Engineering. Start at the beginning to introduce your students to MATLABMATLAB® For Engineers introduces students the MATLAB coding language. Developed out of Moore’s experience teaching MATLAB and other languages, the text meets students at their level of mathematical and computer sophistication. Starting with basic algebra, the book shows how MATLAB can be used to solve a wide range of engineering problems. Examples drawn from concepts introduced in early chemistry and physics classes and freshman and sophomore engineering classes stick to a consistent problem-solving methodology.Students reading this text should have an understanding of college-level algebra and basic trigonometry. The text includes brief backgrounds when introducing new subjects like statistics and matrix algebra. Sections on calculus and differential equations are introduced near the end and can be used for additional reading material for students with more advanced mathematical backgrounds.

Sheldon M. Ross ... 704 pages - Language: ‎English - Publisher: Academic Press; 6th edition (November, 2020).

Introduction to Probability and Statistics for Engineers and Scientists, Sixth Edition, uniquely emphasizes how probability informs statistical problems, thus helping readers develop an intuitive understanding of the statistical procedures commonly used by practicing engineers and scientists. Utilizing real data from actual studies across life science, engineering, computing and business, this useful introduction supports reader comprehension through a wide variety of exercises and examples. End-of-chapter reviews of materials highlight key ideas, also discussing the risks associated with the practical application of each material. In the new edition, coverage includes information on Big Data and the use of R.

This book is intended for upper level undergraduate and graduate students taking a probability and statistics course in engineering programs as well as those across the biological, physical and computer science departments. It is also appropriate for scientists, engineers and other professionals seeking a reference of foundational content and application to these fields.

Provides the author’s uniquely accessible and engaging approach as tailored for the needs of Engineers and Scientists + Features examples that use significant real data from actual studies across life science, engineering, computing and business + Includes new coverage to support the use of R + Offers new chapters on big data techniques.

Helena Barros, Joaquim Figueiras, Carla Ferreira, Mário Pimentel ... 203 pages - Language: ‎English - Publisher: ‎Springer (January, 2022).

This book contains auxiliary calculation tools to facilitate the safety assessment of reinforced concrete sections. Essential parameters in the design to the ultimate limit state of resistance such as the percentage of reinforcement and the position of the neutral axis in concrete cross-sections, as well as the control of the maximum stresses in service limit states are provided by these tools. A set of tables, charts and diagrams used to design cross-sections of reinforced and prestressed concrete structures are supplied. The most current beams and columns cross-sections namely, rectangular, circular and T-sections are considered. These tools have been prepared in line with the provisions of the new European regulations, with particular reference to Eurocode 2 – Design of Concrete Structures.

The book stands as an ideal learning resource for students of structural design and analysis courses in civil engineering, building construction and architecture, as well as a valuablereference for concrete structural design professionals in practice.