5.406 results (0,24855 seconds)

Show all filters

Brand

Merchant

Price (EUR)

Show all

Reset filter

Products
From
Shops

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

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

Hands on Data Science for Biologists Using Python

Hands on Data Science for Biologists Using Python

Hands-on Data Science for Biologists using Python has been conceptualized to address the massive data handling needs of modern-day biologists. With the advent of high throughput technologies and consequent availability of omics data biological science has become a data-intensive field. This hands-on textbook has been written with the inception of easing data analysis by providing an interactive problem-based instructional approach in Python programming language. The book starts with an introduction to Python and steadily delves into scrupulous techniques of data handling preprocessing and visualization. The book concludes with machine learning algorithms and their applications in biological data science. Each topic has an intuitive explanation of concepts and is accompanied with biological examples. Features of this book: The book contains standard templates for data analysis using Python suitable for beginners as well as advanced learners. This book shows working implementations of data handling and machine learning algorithms using real-life biological datasets and problems such as gene expression analysis; disease prediction; image recognition; SNP association with phenotypes and diseases. Considering the importance of visualization for data interpretation especially in biological systems there is a dedicated chapter for the ease of data visualization and plotting. Every chapter is designed to be interactive and is accompanied with Jupyter notebook to prompt readers to practice in their local systems. Other avant-garde component of the book is the inclusion of a machine learning project wherein various machine learning algorithms are applied for the identification of genes associated with age-related disorders. A systematic understanding of data analysis steps has always been an important element for biological research. This book is a readily accessible resource that can be used as a handbook for data analysis as well as a platter of standard code templates for building models. | Hands on Data Science for Biologists Using Python

GBP 69.99
1

Public Policy Analytics Code and Context for Data Science in Government

Public Policy Analytics Code and Context for Data Science in Government

Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why ultimately data science and ‘Planning’ are one and the same. A graduate-level introduction to data science this book will appeal to researchers and data scientists at the intersection of data analytics and public policy as well as readers who wish to understand how algorithms will affect the future of government. | Public Policy Analytics Code and Context for Data Science in Government

GBP 44.99
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

Geospatial Data Science Techniques and Applications

Geospatial Data Science Techniques and Applications

Data science has recently gained much attention for a number of reasons and among them is Big Data. Scientists (from almost all disciplines including physics chemistry biology sociology among others) and engineers (from all fields including civil environmental chemical mechanical among others) are faced with challenges posed by data volume variety and velocity or Big Data. This book is designed to highlight the unique characteristics of geospatial data demonstrate the need to different approaches and techniques for obtaining new knowledge from raw geospatial data and present select state-of-the-art geospatial data science techniques and how they are applied to various geoscience problems. | Geospatial Data Science Techniques and Applications

GBP 44.99
1

Physics of Data Science and Machine Learning

Physics of Data Science and Machine Learning

Physics of Data Science and Machine Learning links fundamental concepts of physics to data science machine learning and artificial intelligence for physicists looking to integrate these techniques into their work. This book is written explicitly for physicists marrying quantum and statistical mechanics with modern data mining data science and machine learning. It also explains how to integrate these techniques into the design of experiments while exploring neural networks and machine learning building on fundamental concepts of statistical and quantum mechanics. This book is a self-learning tool for physicists looking to learn how to utilize data science and machine learning in their research. It will also be of interest to computer scientists and applied mathematicians alongside graduate students looking to understand the basic concepts and foundations of data science machine learning and artificial intelligence. Although specifically written for physicists it will also help provide non-physicists with an opportunity to understand the fundamental concepts from a physics perspective to aid in the development of new and innovative machine learning and artificial intelligence tools. Key Features: Introduces the design of experiments and digital twin concepts in simple lay terms for physicists to understand adopt and adapt. Free from endless derivations; instead equations are presented and it is explained strategically why it is imperative to use them and how they will help in the task at hand. Illustrations and simple explanations help readers visualize and absorb the difficult-to-understand concepts. Ijaz A. Rauf is an adjunct professor at the School of Graduate Studies York University Toronto Canada. He is also an associate researcher at Ryerson University Toronto Canada and president of the Eminent-Tech Corporation Bradford ON Canada.

GBP 56.99
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

Graphical Data Analysis with R

Graphical Data Analysis with R

See How Graphics Reveal InformationGraphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages and the R code is available at rosuda. org/GDA. Graphical data analysis is useful for data cleaning exploring data structure detecting outliers and unusual groups identifying trends and clusters spotting local patterns evaluating modelling output and presenting results. This book guides you in choosing graphics and understanding what information you can glean from them. It can be used as a primary text in a graphical data analysis course or as a supplement in a statistics course. Colour graphics are used throughout.

GBP 42.99
1

Data Analysis and Statistics for Geography Environmental Science and Engineering

Data Analysis and Statistics for Geography Environmental Science and Engineering

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 MethodsBased 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 SolvingEach 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 th

GBP 48.99
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

Advanced Geoinformation Science

Advanced Geoinformation Science

Many of the challenges of the next century will have physical dimensions such as tsunamis hurricanes and climate change as well as human dimensions such as economic crises epidemics and emergency responses. With pioneering editors and expert contributors Advanced Geoinformation Science explores how certain technical aspects of geoinformation have been used and could be used to address such global issues. The editors and chapter authors have been involved in global initiatives such as Global Earth Observation System of Systems (GEOSS) and Digital Earth and research problems such as air quality public health and cloud computing. The book delineates the problems communities are likely to face and how advanced geoinformation science can be a part of their solution. It introduces different methods in collecting spatial data as the initial feeds to geoinformation science and computing platforms. It discusses systems for data management data integration and analysis the geoinformation infrastructure as well as knowledge capture formatting and utilization. The book then explores a variety of geoinformation applications highlighting environmental agriculture and urban planning uses. Geoinformation science encompasses more than just traditional technologies such as Remote Sensing GIS GPS and supporting disciplines. And although the science continues to become more multidisciplinary the literature remains compartmentalized according to the traditional disciplinary boundaries. Capturing recent developments in geoinformation science and linking IT with a wide range of Earth sciences the authors explain how advanced technology and concepts play a significant role in recent advancements. Enhanced with forty-four color illustrations live examples such as GOS and AirNow and insights from NASA EPA and USGS the book provides a vision for the future and explores how to bring that vision into reality.

GBP 74.99
1

Statistical Analysis of Financial Data With Examples In R

Statistical Analysis of Financial Data With Examples In R

Statistical Analysis of Financial Data covers the use of statistical analysis and the methods of data science to model and analyze financial data. The first chapter is an overview of financial markets describing the market operations and using exploratory data analysis to illustrate the nature of financial data. The software used to obtain the data for the examples in the first chapter and for all computations and to produce the graphs is R. However discussion of R is deferred to an appendix to the first chapter where the basics of R especially those most relevant in financial applications are presented and illustrated. The appendix also describes how to use R to obtain current financial data from the internet. Chapter 2 describes the methods of exploratory data analysis especially graphical methods and illustrates them on real financial data. Chapter 3 covers probability distributions useful in financial analysis especially heavy-tailed distributions and describes methods of computer simulation of financial data. Chapter 4 covers basic methods of statistical inference especially the use of linear models in analysis and Chapter 5 describes methods of time series with special emphasis on models and methods applicable to analysis of financial data. Features * Covers statistical methods for analyzing models appropriate for financial data especially models with outliers or heavy-tailed distributions. * Describes both the basics of R and advanced techniques useful in financial data analysis. * Driven by real current financial data not just stale data deposited on some static website. * Includes a large number of exercises many requiring the use of open-source software to acquire real financial data from the internet and to analyze it. | Statistical Analysis of Financial Data With Examples In R

GBP 44.99
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

Joint Models for Longitudinal and Time-to-Event Data With Applications in R

Joint Models for Longitudinal and Time-to-Event Data With Applications in R

In longitudinal studies it is often of interest to investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest e. g. prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R provides a full treatment of random effects joint models for longitudinal and time-to-event outcomes that can be utilized to analyze such data. The content is primarily explanatory focusing on applications of joint modeling but sufficient mathematical details are provided to facilitate understanding of the key features of these models. All illustrations put forward can be implemented in the R programming language via the freely available package JM written by the author. All the R code used in the book is available at:http://jmr. r-forge. r-project. org/ | Joint Models for Longitudinal and Time-to-Event Data With Applications in R

GBP 42.99
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

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization describes such algorithms as Locally Linear Embedding (LLE) Laplacian Eigenmaps Isomap Semidefinite Embedding and t-SNE to resolve the problem of dimensionality reduction in the case of non-linear relationships within the data. Underlying mathematical concepts derivations and proofs with logical explanations for these algorithms are discussed including strengths and limitations. The book highlights important use cases of these algorithms and provides examples along with visualizations. Comparative study of the algorithms is presented to give a clear idea on selecting the best suitable algorithm for a given dataset for efficient dimensionality reduction and data visualization. FEATURES Demonstrates how unsupervised learning approaches can be used for dimensionality reduction Neatly explains algorithms with a focus on the fundamentals and underlying mathematical concepts Describes the comparative study of the algorithms and discusses when and where each algorithm is best suitable for use Provides use cases illustrative examples and visualizations of each algorithm Helps visualize and create compact representations of high dimensional and intricate data for various real-world applications and data analysis This book is aimed at professionals graduate students and researchers in Computer Science and Engineering Data Science Machine Learning Computer Vision Data Mining Deep Learning Sensor Data Filtering Feature Extraction for Control Systems and Medical Instruments Input Extraction.

GBP 56.99
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

Environmental Science and Technology A Sustainable Approach to Green Science and Technology Second Edition

Environmental Science and Technology A Sustainable Approach to Green Science and Technology Second Edition

Formally established by the EPA nearly 15 years ago the concept of green chemistry is beginning to come of age. Although several books cover green chemistry and chemical engineering none of them transfer green principles to science and technology in general and their impact on the future. Defining industrial ecology Environmental Science and Technology: A Sustainable Approach to Green Science and Technology provides a general overview of green science and technology and their essential role in ensuring environmental sustainability. Written by a leading expert the book provides the essential background for understanding green science and technology and how they relate to sustainability. In addition to the hydrosphere atmosphere geosphere and biosphere traditionally covered in environmental science books this book is unique in recognizing the anthrosphere as a distinct sphere of the environment. The author explains how the anthrosphere can be designed and operated in a manner that does not degrade environmental quality and in most favorable circumstances may even enhance it. With the current emphasis shifting from end-of-pipe solutions to pollution prevention and control of resource consumption green principles are increasingly moving into the mainstream. This book provides the foundation not only for understanding green science and technology but also for taking its application to the next level. | Environmental Science and Technology A Sustainable Approach to Green Science and Technology Second Edition

GBP 59.99
1

Real-World Software Projects for Computer Science and Engineering Students

Real-World Software Projects for Computer Science and Engineering Students

Developing projects outside of a classroom setting can be intimidating for students and is not always a seamless process. Real-World Software Projects for Computer Science and Engineering Students is a quick easy source for tackling such issues. Filling a critical gap in the research literature the book: Is ideal for academic project supervisors. Helps researchers conduct interdisciplinary research. Guides computer science students on undertaking and implementing research-based projects This book explains how to develop highly complex industry-specific projects touching on real-world complexities of software developments. It shows how to develop projects for students who have not yet had the chance to gain real-world experience providing opportunity to become familiar with the skills needed to implement projects using standard development methodologies. The book is also a great source for teachers of undergraduate students in software engineering and computer science as it can help students prepare for the risk and uncertainty that is typical of software development in industrial settings.

GBP 56.99
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

Handbook of Science Communication

Handbook of Science Communication

Addressing the lack of a specific book on core communication/presentation skills the Handbook of Science Communication is written as a guide for students to speak and write effectively and as a reference for scientists who need to communicate their work effectively to each other and to the wider public. The book considers how the public understanding of science has changed with time and clearly explains how important the art of communication is for the effective communication of ideas. It continues with guidance on literature searches and the use of information sources from the library to the live interviewee. The book also deals with how to write and speak effectively working in a group and working with the media.

GBP 175.00
1

Vacuum Science Technology and Applications

Vacuum Science Technology and Applications

Vacuum plays an important role in science and technology. The study of interaction of charged particles neutrals and radiation with each other and with solid surfaces requires a vacuum environment for reliable investigations. Vacuum has contributed to major advancements made in nuclear science space metallurgy electrical/electronic technology chemical engineering transportation robotics and many other fields. This book is intended to assist students scientists technicians and engineers with understanding the basics of vacuum science and technology for application in their projects. The fundamental theories concepts devices applications and key inventions are discussed. | Vacuum Science Technology and Applications

GBP 44.99
1