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Data Science for Engineers

Data Science for Engineers

With tremendous improvement in computational power and availability of rich data almost all engineering disciplines use data science at some level. This textbook presents material on data science comprehensively and in a structured manner. It provides conceptual understanding of the fields of data science machine learning and artificial intelligence with enough level of mathematical details necessary for the readers. This will help readers understand major thematic ideas in data science machine learning and artificial intelligence and implement first-level data science solutions to practical engineering problems. The book- Provides a systematic approach for understanding data science techniques Explain why machine learning techniques are able to cross-cut several disciplines. Covers topics including statistics linear algebra and optimization from a data science perspective. Provides multiple examples to explain the underlying ideas in machine learning algorithms Describes several contemporary machine learning algorithms The textbook is primarily written for undergraduate and senior undergraduate students in different engineering disciplines including chemical engineering mechanical engineering electrical engineering electronics and communications engineering for courses on data science machine learning and artificial intelligence. | Data Science for Engineers

GBP 89.99
1

The Essentials of Data Science: Knowledge Discovery Using R

The Essentials of Data Science: Knowledge Discovery Using R

The Essentials of Data Science: Knowledge Discovery Using R presents the concepts of data science through a hands-on approach using free and open source software. It systematically drives an accessible journey through data analysis and machine learning to discover and share knowledge from data. Building on over thirty years’ experience in teaching and practising data science the author encourages a programming-by-example approach to ensure students and practitioners attune to the practise of data science while building their data skills. Proven frameworks are provided as reusable templates. Real world case studies then provide insight for the data scientist to swiftly adapt the templates to new tasks and datasets. The book begins by introducing data science. It then reviews R’s capabilities for analysing data by writing computer programs. These programs are developed and explained step by step. From analysing and visualising data the framework moves on to tried and tested machine learning techniques for predictive modelling and knowledge discovery. Literate programming and a consistent style are a focus throughout the book.

GBP 145.00
1

Data Science for Effective Healthcare Systems

Data Science for Effective Healthcare Systems

Data Science for Effective Healthcare Systems has a prime focus on the importance of data science in the healthcare domain. Various applications of data science in the health care domain have been studied to find possible solutions. In this period of COVID-19 pandemic data science and allied areas plays a vital role to deal with various aspect of health care. Image processing detection & prevention from COVID-19 virus drug discovery early prediction and prevention of diseases are some thrust areas where data science has proven to be indispensable. Key Features: The book offers comprehensive coverage of the most essential topics including: Big Data Analytics Applications & Challenges in Healthcare Descriptive Predictive and Prescriptive Analytics in Healthcare Artificial Intelligence Machine Learning Deep Learning and IoT in Healthcare Data Science in Covid-19 Diabetes Coronary Heart Diseases Breast Cancer Brain Tumor The aim of this book is also to provide the future scope of these technologies in the health care domain. Last but not the least this book will surely benefit research scholar persons associated with healthcare faculty research organizations and students to get insights into these emerging technologies in the healthcare domain.

GBP 110.00
1

Fundamentals of Data Science

Fundamentals of Data Science

Fundamentals of Data Science is designed for students academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts techniques and tools required to understand Data Science. Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect aggregate process and gain insights from massive datasets. This book offers all the processes methodologies various steps like data acquisition pre-process mining prediction and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods algorithms and processes Readers will learn the steps necessary to create the application with SQl NoSQL Python R Matlab Octave and Tablue. This book provides a stepwise approach to building solutions to data science applications right from understanding the fundamentals performing data analytics to writing source code. All the concepts are discussed in simple English to help the community to become Data Scientist without much pre-requisite knowledge. Features : Simple strategies for developing statistical models that analyze data and detect patterns trends and relationships in data sets. Complete roadmap to Data Science approach with dedicatedsections which includes Fundamentals Methodology and Tools. Focussed approach for learning and practice various Data Science Toolswith Sample code and examples for practice. Information is presented in an accessible way for students researchers and academicians and professionals.

GBP 120.00
1

Data Science Techniques and Intelligent Applications

Data Science Techniques and Intelligent Applications

This book covers the topic of data science in a comprehensive manner and synthesizes both fundamental and advanced topics of a research area that has now reached its maturity. The book starts with the basic concepts of data science. It highlights the types of data and their use and importance followed by a discussion on a wide range of applications of data science and widely used techniques in data science. Key Features • Provides an internationally respected collection of scientific research methods technologies and applications in the area of data science. • Presents predictive outcomes by applying data science techniques to real-life applications. • Provides readers with the tools techniques and cases required to excel with modern artificial intelligence methods. • Gives the reader a variety of intelligent applications that can be designed using data science and its allied fields. The book is aimed primarily at advanced undergraduates and graduates studying machine learning and data science. Researchers and professionals will also find this book useful. | Data Science Techniques and Intelligent Applications

GBP 130.00
1

Data Science for Mathematicians

Data Science for Mathematicians

Mathematicians have skills that if deepened in the right ways would enable them to use data to answer questions important to them and others and report those answers in compelling ways. Data science combines parts of mathematics statistics computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science. As it applies to the curriculum research and career opportunities data science is a fast-growing field. Contributors from both academics and industry present their views on these opportunities and how to advantage them. | Data Science for Mathematicians

GBP 150.00
1

Data Science and Innovations for Intelligent Systems Computational Excellence and Society 5.0

Data Science and Innovations for Intelligent Systems Computational Excellence and Society 5.0

Data science is an emerging field and innovations in it need to be explored for the success of society 5. 0. This book not only focuses on the practical applications of data science to achieve computational excellence but also digs deep into the issues and implications of intelligent systems. This book highlights innovations in data science to achieve computational excellence that can optimize performance of smart applications. The book focuses on methodologies framework design issues tools architectures and technologies necessary to develop and understand data science and its emerging applications in the present era. Data Science and Innovations for Intelligent Systems: Computational Excellence and Society 5. 0 is useful for the research community start-up entrepreneurs academicians data-centered industries and professeurs who are interested in exploring innovations in varied applications and the areas of data science. | Data Science and Innovations for Intelligent Systems Computational Excellence and Society 5. 0

GBP 130.00
1

Data Science with Semantic Technologies Deployment and Exploration

Data Science with Semantic Technologies Deployment and Exploration

Gone are the days when data was interlinked with related data by humans and human interpretation was required. Data is no longer just data. It is now considered a Thing or Entity or Concept with meaning so that a machine not only understands the concept but also extrapolates the way humans do. Data Science with Semantic Technologies: Deployment and Exploration the second volume of a two-volume handbook set provides a roadmap for the deployment of semantic technologies in the field of data science and enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame. In addition this book offers the answer to various questions like: What makes a technology semantic as opposed to other approaches to data science? What is knowledge data science? How does knowledge data science relate to other fields? This book explores the optimal use of these technologies to provide the highest benefit to the user under one comprehensive source and title. As there is no dedicated book available in the market on this topic at this time this book becomes a unique resource for scholars researchers data scientists professionals and practitioners. This volume can serve as an important guide toward applications of data science with semantic technologies for the upcoming generation. | Data Science with Semantic Technologies Deployment and Exploration

GBP 150.00
1

Time Series for Data Science Analysis and Forecasting

Time Series for Data Science Analysis and Forecasting

Data Science students and practitioners want to find a forecast that “works” and don’t want to be constrained to a single forecasting strategy Time Series for Data Science: Analysis and Forecasting discusses techniques of ensemble modelling for combining information from several strategies. Covering time series regression models exponential smoothing Holt-Winters forecasting and Neural Networks. It places a particular emphasis on classical ARMA and ARIMA models that is often lacking from other textbooks on the subject. This book is an accessible guide that doesn’t require a background in calculus to be engaging but does not shy away from deeper explanations of the techniques discussed. Features: Provides a thorough coverage and comparison of a wide array of time series models and methods: Exponential Smoothing Holt Winters ARMA and ARIMA deep learning models including RNNs LSTMs GRUs and ensemble models composed of combinations of these models. Introduces the factor table representation of ARMA and ARIMA models. This representation is not available in any other book at this level and is extremely useful in both practice and pedagogy. Uses real world examples that can be readily found via web links from sources such as the US Bureau of Statistics Department of Transportation and the World Bank. There is an accompanying R package that is easy to use and requires little or no previous R experience. The package implements the wide variety of models and methods presented in the book and has tremendous pedagogical use. | Time Series for Data Science Analysis and Forecasting

GBP 99.99
1

Data Science AI and Machine Learning in Drug Development

Data Science AI and Machine Learning in Drug Development

The confluence of big data artificial intelligence (AI) and machine learning (ML) has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances it is essential to systematically harness data from diverse sources and leverage digital technologies and advanced analytics to enable data-driven decisions. Data science stands at a unique moment of opportunity to lead such a transformative change. Intended to be a single source of information Data Science AI and Machine Learning in Drug Research and Development covers a wide range of topics on the changing landscape of drug R & D emerging applications of big data AI and ML in drug development and the build of robust data science organizations to drive biopharmaceutical digital transformations. Features Provides a comprehensive review of challenges and opportunities as related to the applications of big data AI and ML in the entire spectrum of drug R & D Discusses regulatory developments in leveraging big data and advanced analytics in drug review and approval Offers a balanced approach to data science organization build Presents real-world examples of AI-powered solutions to a host of issues in the lifecycle of drug development Affords sufficient context for each problem and provides a detailed description of solutions suitable for practitioners with limited data science expertise | Data Science AI and Machine Learning in Drug Development

GBP 99.99
1

Recent Trends in Computational Sciences Proceedings of the Fourth Annual International Conference on Data Science Machine Learning and Bloc

Recent Trends in Computational Sciences Proceedings of the Fourth Annual International Conference on Data Science Machine Learning and Bloc

This book is a compilation of research papers and presentations from the Fourth Annual International Conference on Data Science Machine Learning and Blockchain Technology (AICDMB 2023 Mysuru India 16-17 March 2023). The book covers a wide range of topics including data mining natural language processing deep learning computer vision big data analytics cryptography smart contracts decentralized applications and blockchain-based solutions for various industries such as healthcare finance and supply chain management. The research papers presented in this book highlight the latest advancements and practical applications in data science machine learning and blockchain technology and provide insights into the future direction of these fields. The book serves as a valuable resource for researchers students and professionals in the areas of data science machine learning and blockchain technology. | Recent Trends in Computational Sciences Proceedings of the Fourth Annual International Conference on Data Science Machine Learning and Bloc

GBP 94.99
1

God and the Book of Nature Experiments in Theology of Science

God and the Book of Nature Experiments in Theology of Science

God and the Book of Nature develops theological views of the natural sciences in light of the recent theological turn in science-and-religion scholarship and the ‘science-engaged theology’ movement. Centered around the Book of Nature metaphor it brings together contributions by theologians natural scientists and philosophers based in Europe and North America. They provide an exploration of complementary (and even contesting) readings of the Book of Nature particularly in light of the vexing questions that arise around essentialism and unity in the field of science and religion. Taking an experimental and open-ended approach the volume does not attempt to unify the readings into a single ‘plot’ that defines the Book of Nature still less a single ‘theology of nature’ but instead it represents a variety of hermeneutical stances. Overall the book embraces a constructive theological attitude toward the modern sciences and makes significant contributions to the research literature in science and religion. | God and the Book of Nature Experiments in Theology of Science

GBP 130.00
1

Remote Sensing Data Analysis in R

Remote Sensing Data Analysis in R

Remote Sensing Data Analysis in R is a guide book containing codes for most of the operations which are being performed for analysing any satellite data for deriving meaningful information. The goal of this book is to provide hands on experience in performing all the activities from the loading of raster and vector data mapping or visualisation of data pre-processing calculation of indices classification and advanced machine learning algorithms on remote sensing data in R. The reader will be able to acquire skills to carry out most of the operations of raster data analysis – more flexibly - in open-source freely available software i. e. R which are generally available in the paid digital image processing software. Note: T& F does not sell or distribute the Hardback in India Pakistan Nepal Bhutan Bangladesh and Sri Lanka. The title is co-published with New India Publishing Agency.

GBP 89.99
1

Handbook of Fractional Calculus for Engineering and Science

Handbook of Fractional Calculus for Engineering and Science

Fractional calculus is used to model many real-life situations from science and engineering. The book includes different topics associated with such equations and their relevance and significance in various scientific areas of study and research. In this book readers will find several important and useful methods and techniques for solving various types of fractional-order models in science and engineering. The book should be useful for graduate students PhD students researchers and educators interested in mathematical modelling physical sciences engineering sciences applied mathematical sciences applied sciences and so on. This Handbook: Provides reliable methods for solving fractional-order models in science and engineering. Contains efficient numerical methods and algorithms for engineering-related equations. Contains comparison of various methods for accuracy and validity. Demonstrates the applicability of fractional calculus in science and engineering. Examines qualitative as well as quantitative properties of solutions of various types of science- and engineering-related equations. Readers will find this book to be useful and valuable in increasing and updating their knowledge in this field and will be it will be helpful for engineers mathematicians scientist and researchers working on various real-life problems. | Handbook of Fractional Calculus for Engineering and Science

GBP 150.00
1

Stochastic Differential Equations for Science and Engineering

Stochastic Differential Equations for Science and Engineering

Stochastic Differential Equations for Science and Engineering is aimed at students at the M. Sc. and PhD level. The book describes the mathematical construction of stochastic differential equations with a level of detail suitable to the audience while also discussing applications to estimation stability analysis and control. The book includes numerous examples and challenging exercises. Computational aspects are central to the approach taken in the book so the text is accompanied by a repository on GitHub containing a toolbox in R which implements algorithms described in the book code that regenerates all figures and solutions to exercises. Features: Contains numerous exercises examples and applications Suitable for science and engineering students at Master’s or PhD level Thorough treatment of the mathematical theory combined with an accessible treatment of motivating examples GitHub repository available at: https://github. com/Uffe-H-Thygesen/SDEbook and https://github. com/Uffe-H-Thygesen/SDEtools

GBP 89.99
1

Data Structures using C A Practical Approach for Beginners

Data Structures using C A Practical Approach for Beginners

The data structure is a set of specially organized data elements and functions which are defined to store retrieve remove and search for individual data elements. Data Structures using C: A Practical Approach for Beginners covers all issues related to the amount of storage needed the amount of time required to process the data data representation of the primary memory and operations carried out with such data. Data Structures using C: A Practical Approach for Beginners book will help students learn data structure and algorithms in a focused way. Resolves linear and nonlinear data structures in C language using the algorithm diagrammatically and its time and space complexity analysis Covers interview questions and MCQs on all topics of campus readiness Identifies possible solutions to each problem Includes real-life and computational applications of linear and nonlinear data structures This book is primarily aimed at undergraduates and graduates of computer science and information technology. Students of all engineering disciplines will also find this book useful. | Data Structures using C A Practical Approach for Beginners

GBP 105.00
1

Students’ Motivations and Emotions in Chinese Science Classrooms

Students’ Motivations and Emotions in Chinese Science Classrooms

The book reviews and examines students’ motivations and emotions in Chinese science classrooms. By adopting different approaches such as content analysis factor analysis path analysis and latent profile analysis the author analyzes the content of literature curriculum standards and textbooks classroom observations survey data interview data and open-ended responses from students and teachers through a literature review and six empirical studies. The findings may provide insights for education researchers and practitioners seeking to improve science teachers’ pedagogical practices and create friendlier classroom environments. Researchers of science education or those who are interested in investigating students’ affective perceptions in specific subject contexts will find this book interesting.

GBP 130.00
1

Practical Handbook of Earth Science

Practical Handbook of Earth Science

This self-contained handbook provides a carefully researched compact source of key earth science information and data logically sorted by subject matter and then cross-referenced. Appealing to both experts and non-experts alike the book presents earth science and environmental science as closely intertwined. It includes tables of the global distributions of fossil fuels contrasted by tables of the distribution of non-fossil energy sources. Concise explanations cover the subject matters of geology geophysics oceans atmosphere with attention to environmental implications and resources. | Practical Handbook of Earth Science

GBP 89.99
1

Machine Learning in 2D Materials Science

Machine Learning in 2D Materials Science

Data science and machine learning (ML) methods are increasingly being used to transform the way research is being conducted in materials science to enable new discoveries and design new materials. For any materials science researcher or student it may be daunting to figure out if ML techniques are useful for them or if so which ones are applicable in their individual contexts and how to study the effectiveness of these methods systematically. KEY FEATURES Provides broad coverage of data science and ML fundamentals to materials science researchers so that they can confidently leverage these techniques in their research projects Offers introductory material in topics such as ML data integration and 2D materials Provides in-depth coverage of current ML methods for validating 2D materials using both experimental and simulation data researching and discovering new 2D materials and enhancing ML methods with physical properties of materials Discusses customized ML methods for 2D materials data and applications and high-throughput data acquisition Describes several case studies illustrating how ML approaches are currently leading innovations in the discovery development manufacturing and deployment of 2D materials needed for strengthening industrial products Gives future trends in ML for 2D materials explainable AI and dealing with extremely large and small diverse datasets Aimed at materials science researchers this book allows readers to quickly yet thoroughly learn the ML and AI concepts needed to ascertain the applicability of ML methods in their research. | Machine Learning in 2D Materials Science

GBP 110.00
1

Big Data for Entrepreneurship and Sustainable Development

Big Data for Entrepreneurship and Sustainable Development

This book provides insight for researchers and decision-makers on the application of data in the entrepreneurship and sustainable development sector. This book covers how Big Data for Industry 4. 0 and entrepreneurship are effective in resolving business social and economic problems. The book discusses how entrepreneurs use Big Data to cut costs and minimize the waste of time. It offers how using Big Data can increase efficiency enables the studying of competitors can improve the pricing of products increase sales and loyalty and can ensure the right people are hired. The book presents how decision-makers can make use of Big Data to resolve economic and social problems. Analyze the development of the economy and enhance the business climate. This book is for researchers PhD students and entrepreneurs and can also be of interest for transforming governments as well as businesses. | Big Data for Entrepreneurship and Sustainable Development

GBP 130.00
1

IoT and Big Data Analytics for Smart Cities A Global Perspective

IoT and Big Data Analytics for Smart Cities A Global Perspective

The book IoT and Big Data Analytics (IoT-BDA) for Smart Cities – A Global Perspective emphasizes the challenges architectural models and intelligent frameworks with smart decisionmaking systems using Big Data and IoT with case studies. The book illustrates the benefits of Big Data and IoT methods in framing smart systems for smart applications. The text is a coordinated amalgamation of research contributions and industrial applications in the field of smart cities. Features: Provides the necessity of convergence of Big Data Analytics and IoT techniques in smart city application Challenges and Roles of IoT and Big Data in Smart City applications Provides Big Data-IoT intelligent smart systems in a global perspective Provides a predictive framework that can handle the traffic on abnormal days such as weekends and festival holidays Gives various solutions and ideas for smart traffic development in smart cities Gives a brief idea of the available algorithms/techniques of Big Data and IoT and guides in developing a solution for smart city applications This book is primarily aimed at IT professionals. Undergraduates graduates and researchers in the area of computer science and information technology will also find this book useful. | IoT and Big Data Analytics for Smart Cities A Global Perspective

GBP 110.00
1

Visualizing Surveys in R

Visualizing Surveys in R

Visualizing Surveys in R is about creating static print quality figures from survey data using R. The focus is not for example on statistical analysis of survey data but rather on giving concrete solutions for typical problems in visualizing survey data. While there are many excellent books on data visualization surveys and R the aim of this book is to bring these topics together and offer practical instructions for visualizing surveys in R. Features Introduction to survey data: variables categories and scales Description of a process for visualizing survey data Recommendations for reading survey data into R Advice on building a survey dataset in R to facilitate versatile plotting Step-by-step recipes in R for creating useful plots from survey data The book is intended for researchers who regularly use surveys and are interested in learning how to seize the vast possibilities and the flexibility of R in survey analysis and visualizations. The book is also valuable for psychologists marketeers HR personnel managers and other professionals who wish to standardize and automate the process for visualizing survey data. Finally the book is suitable as a course textbook either more widely on survey studies or more strictly on visualizing survey data in R.

GBP 140.00
1

Social Data Analytics

Social Data Analytics

This book is an introduction to social data analytics along with its challenges and opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on concepts techniques and methods for organizing curating processing analyzing and visualizing big social data: from text to image and video analytics. It provides novel techniques in storytelling with social data to facilitate the knowledge and fact discovery. The book covers a large body of knowledge that will help practitioners and researchers in understanding the underlying concepts problems methods tools and techniques involved in modern social data analytics. It also provides real-world applications of social data analytics including: Sales and Marketing Influence Maximization Situational Awareness customer success and Segmentation and performance analysis of the industry. It provides a deep knowledge in social data analytics by comprehensively classifying the current state of research by describing in-depth techniques and methods and by highlighting future research directions. Lecturers will find a wealth of material to choose from for a variety of courses ranging from undergraduate courses in data science to graduate courses in data analytics.

GBP 145.00
1

Structural Equation Modeling Using R/SAS A Step-by-Step Approach with Real Data Analysis

Structural Equation Modeling Using R/SAS A Step-by-Step Approach with Real Data Analysis

There has been considerable attention to making the methodologies of structural equation modeling available to researchers practitioners and students along with commonly used software. Structural Equation Modelling Using R/SAS aims to bring it all together to provide a concise point-of-reference for the most commonly used structural equation modeling from the fundamental level to the advanced level. This book is intended to contribute to the rapid development in structural equation modeling and its applications to real-world data. Straightforward explanations of the statistical theory and models related to structural equation models are provided using a compilation of a variety of publicly available data to provide an illustration of data analytics in a step-by-step fashion using commonly used statistical software of R and SAS. This book is appropriate for anyone who is interested in learning and practicing structural equation modeling especially in using R and SAS. It is useful for applied statisticians data scientists and practitioners applied statistical analysts and scientists in public health and academic researchers and graduate students in statistics whilst also being of use to R&D professionals/practitioners in industry and governmental agencies. Key Features: Extensive compilation of commonly used structural equation models and methods from fundamental to advanced levels Straightforward explanations of the theory related to the structural equation models Compilation of a variety of publicly available data Step-by-step illustrations of data analysis using commonly used statistical software R and SAS Data and computer programs are available for readers to replicate and implement the new methods to better understand the book contents and for future applications Handbook for applied statisticians and practitioners | Structural Equation Modeling Using R/SAS A Step-by-Step Approach with Real Data Analysis

GBP 89.99
1