Engineering Data Analysis With Matlab R

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Engineering Data Analysis With Matlab

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Author : Tanvir Mustafy
language : en
Publisher: CRC Press
Release Date : 2024-12-30

Engineering Data Analysis With Matlab written by Tanvir Mustafy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Mathematics categories.

This book provides a concise overview of a variety of techniques for analyzing statistical, scientific, and financial data, using MATLAB® to integrate several approaches to data analysis and statistics. The chapters offer a broad review of computational data analysis, illustrated with many examples and applications. Topics range from the basics of data and statistical analysis to more advanced subjects such as probability distributions, descriptive and inferential statistics, parametric and non-parametric tests, correlation, and regression analysis. Each chapter combines theoretical concepts with practical MATLAB® applications and includes practice exercises, ensuring a comprehensive understanding of the material. With coverage of both basic and more complex ideas in applied statistics, the book has broad appeal for undergraduate students up to practicing engineers.

Using R For Numerical Analysis In Science And Engineering

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Author : Victor A. Bloomfield
language : en
Publisher: CRC Press
Release Date : 2018-09-03

Using R For Numerical Analysis In Science And Engineering written by Victor A. Bloomfield and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Mathematics categories.

Instead of presenting the standard theoretical treatments that underlie the various numerical methods used by scientists and engineers, Using R for Numerical Analysis in Science and Engineering shows how to use R and its add-on packages to obtain numerical solutions to the complex mathematical problems commonly faced by scientists and engineers. This practical guide to the capabilities of R demonstrates Monte Carlo, stochastic, deterministic, and other numerical methods through an abundance of worked examples and code, covering the solution of systems of linear algebraic equations and nonlinear equations as well as ordinary differential equations and partial differential equations. It not only shows how to use R’s powerful graphic tools to construct the types of plots most useful in scientific and engineering work, but also: Explains how to statistically analyze and fit data to linear and nonlinear models Explores numerical differentiation, integration, and optimization Describes how to find eigenvalues and eigenfunctions Discusses interpolation and curve fitting Considers the analysis of time series Using R for Numerical Analysis in Science and Engineering provides a solid introduction to the most useful numerical methods for scientific and engineering data analysis using R.

Predictive Analytics Using Matlab R For Biomedical Applications

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Author : L. Ashok Kumar
language : en
Publisher: Elsevier
Release Date : 2024-10-03

Predictive Analytics Using Matlab R For Biomedical Applications written by L. Ashok Kumar and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-03 with Science categories.

Predictive Analytics using MATLAB(R) for Biomedical Applications is a comprehensive and practical guide for biomedical engineers, data scientists, and researchers on how to use predictive analytics techniques in MATLAB(R) for solving real-world biomedical problems. The book offers a technical overview of various predictive analytics methods and covers the utilization of MATLAB(R) for implementing these techniques. It includes several case studies that demonstrate how predictive analytics can be applied to real-world biomedical problems, such as predicting disease progression, analyzing medical imaging data, and optimizing treatment outcomes.With a plethora of examples and exercises, this book is the ultimate tool for reinforcing one's knowledge and skills. - Covers various predictive analytics methods, including regression analysis, time series analysis, and machine learning algorithms, providing readers with a comprehensive understanding of the field - Provides a hands-on approach to learning predictive analytics, with a focus on practical applications in biomedical engineering - Includes several case studies that demonstrate the practical application of predictive analytics in real-world biomedical problems, such as disease progression prediction, medical imaging analysis, and treatment optimization

Data Analysis And Statistics For Geography Environmental Science And Engineering

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Author : Miguel F. Acevedo
language : en
Publisher: CRC Press
Release Date : 2012-12-07

Data Analysis And Statistics For Geography Environmental Science And Engineering written by Miguel F. Acevedo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-07 with Mathematics categories.

Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustainability, the book brings together principles of statistics and probability, multivariate analysis, and spatial analysis methods applicable across a variety of science and engineering disciplines. Learn How to Use a Variety of Data Analysis and Statistics Methods Based on the author’s many years of teaching graduate and undergraduate students, this textbook emphasizes hands-on learning. Organized into two parts, it allows greater flexibility using the material in various countries and types of curricula. The first part covers probability, random variables and inferential statistics, applications of regression, time series analysis, and analysis of spatial point patterns. The second part uses matrix algebra to address multidimensional problems. After a review of matrices, it delves into multiple regression, dependent random processes and autoregressive time series, spatial analysis using geostatistics and spatial regression, discriminant analysis, and a variety of multivariate analyses based on eigenvector methods. Build from Fundamental Concepts to Effective Problem Solving Each chapter starts with conceptual and theoretical material to give a firm foundation in how the methods work. Examples and exercises illustrate the applications and demonstrate how to go from concepts to problem solving. Hands-on computer sessions allow students to grasp the practical implications and learn by doing. Throughout, the computer examples and exercises use seeg and RcmdrPlugin.seeg, open-source R packages developed by the author, which help students acquire the skills to implement and conduct analysis and to analyze the results. This self-contained book offers a unified presentation of data analysis methods for more effective problem solving. With clear, easy-to-follow explanations, the book helps students to develop a solid understanding of basic statistical analysis and prepares them for learning the more advanced and specialized methods they will need in their work.

Essential Interpersonal Skills For Engineers

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Author : MS. NEHA BAKSHI
language : en
Publisher: JEC PUBLICATION
Release Date :

Essential Interpersonal Skills For Engineers written by MS. NEHA BAKSHI and has been published by JEC PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Psychology categories.

In this rapidly evolving world, where technology reshapes landscapes and redefines boundaries, the role of engineers has never been more pivotal. As creators and innovators, engineers are at the forefront of constructing the very foundation of our modern society. However, the complexity of this role transcends mere technical skills and knowledge. It demands a keen understanding of teamwork, leadership, ethics, and communication—elements that are crucial for success yet often overshadowed by technical prowess. This book, Essential Interpersonal Skills for Engineers, aims to bridge this gap by focusing on the soft skills and strategic frameworks that are essential for contemporary engineers. The journey of an engineer is one of constant learning and adaptation. Whether you are a student embarking on your educational path, a seasoned professional steering complex projects, or anywhere in between, the need to refine and enhance your soft skills remains constant. This book has been meticulously crafted to serve as a comprehensive guide, offering insights, strategies, and practical advice to help engineers navigate their professional landscapes more effectively. Throughout the chapters, we delve into various aspects of professional development, including effective communication, both verbal and non-verbal; project management skills that cover planning to execution; leadership styles that suit different team dynamics and project needs; and the ethical responsibilities that come with the engineering mantle. We explore how emotional intelligence shapes interactions and decisions, the importance of teamwork and collaboration, and the perpetual need for innovation and adaptability in the face of new challenges.

Data Analytics For Intelligent Transportation Systems

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Author : Mashrur Chowdhury
language : en
Publisher: Elsevier
Release Date : 2024-11-02

Data Analytics For Intelligent Transportation Systems written by Mashrur Chowdhury and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-02 with Computers categories.

Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. It presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies. All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. They will discover how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Data Analytics for Intelligent Transportation Systems will prepare an educated ITS workforce and tool builders to make the vision for safe, reliable, and environmentally sustainable intelligent transportation systems a reality. It serves as a primary or supplemental textbook for upper-level undergraduate and graduate ITS courses and a valuable reference for ITS practitioners. - Utilizes real ITS examples to facilitate a quicker grasp of materials presented - Contains contributors from both leading academic and commercial domains - Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications - Includes exercise problems in each chapter to help readers apply and master the learned fundamentals, concepts, and techniques - New to the second edition: Two new chapters on Quantum Computing in Data Analytics and Society and Environment in ITS Data Analytics

Data Driven Model Learning For Engineers

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Author : Guillaume Mercère
language : en
Publisher: Springer Nature
Release Date : 2023-08-09

Data Driven Model Learning For Engineers written by Guillaume Mercère and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-09 with Mathematics categories.

The main goal of this comprehensive textbook is to cover the core techniques required to understand some of the basic and most popular model learning algorithms available for engineers, then illustrate their applicability directly with stationary time series. A multi-step approach is introduced for modeling time series which differs from the mainstream in the literature. Singular spectrum analysis of univariate time series, trend and seasonality modeling with least squares and residual analysis, and modeling with ARMA models are discussed in more detail. As applications of data-driven model learning become widespread in society, engineers need to understand its underlying principles, then the skills to develop and use the resulting data-driven model learning solutions. After reading this book, the users will have acquired the background, the knowledge and confidence to (i) read other model learning textbooks more easily, (ii) use linear algebra and statistics for data analysis and modeling, (iii) explore other fields of applications where model learning from data plays a central role. Thanks to numerous illustrations and simulations, this textbook will appeal to undergraduate and graduate students who need a first course in data-driven model learning. It will also be useful for practitioners, thanks to the introduction of easy-to-implement recipes dedicated to stationary time series model learning. Only a basic familiarity with advanced calculus, linear algebra and statistics is assumed, making the material accessible to students at the advanced undergraduate level.

Foundations Of Data Science For Engineering Problem Solving

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Author : Parikshit Narendra Mahalle
language : en
Publisher: Springer Nature
Release Date : 2021-08-21

Foundations Of Data Science For Engineering Problem Solving written by Parikshit Narendra Mahalle and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-21 with Technology & Engineering categories.

This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.

Advanced Deep Learning Applications In Big Data Analytics

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Author : Bouarara, Hadj Ahmed
language : en
Publisher: IGI Global
Release Date : 2020-10-16

Advanced Deep Learning Applications In Big Data Analytics written by Bouarara, Hadj Ahmed and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-16 with Computers categories.

Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.

Full Source Code Sql Server For Data Analytics And Visualization With Python Gui

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Author : Vivian Siahaan
language : en
Publisher: BALIGE PUBLISHING
Release Date : 2022-10-06

Full Source Code Sql Server For Data Analytics And Visualization With Python Gui written by Vivian Siahaan and has been published by BALIGE PUBLISHING this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-06 with Computers categories.

This book uses SQL SERVER version of MySQL-based Sakila sample database. It is a fictitious database designed to represent a DVD rental store. The tables of the database include film, film_category, actor, customer, rental, payment and inventory among others. The Sakila sample database is intended to provide a standard schema that can be used for examples in books, tutorials, articles, samples, and so forth. Detailed information about the database can be found on website: https://dev.mysql.com/doc/index-other.html. In this project, you will develop GUI using PyQt5 to: read SQL SERVER database and every table in it; read every actor in actor table, read every film in films table; plot case distribution of film release year, film rating, rental duration, and categorize film length; plot rating variable against rental_duration variable in stacked bar plots; plot length variable against rental_duration variable in stacked bar plots; read payment table; plot case distribution of Year, Day, Month, Week, and Quarter of payment; plot which year, month, week, days of week, and quarter have most payment amount; read film list by joining five tables: category, film_category, film_actor, film, and actor; plot case distribution of top 10 and bottom 10 actors; plot which film title have least and most sales; plot which actor have least and most sales; plot which film category have least and most sales; plot case distribution of top 10 and bottom 10 overdue customers; plot which customer have least and most overdue days; plot which store have most sales; plot average payment amount by month with mean and EWM; and plot payment amount over June 2005.