153 results (0,23304 seconds)

Show all filters

Brand

Merchant

Price (EUR)

Reset filter

Products
From
Shops

Cloud Security Attacks Techniques Tools and Challenges

Cloud Security Attacks Techniques Tools and Challenges

Cloud computing has gained paramount attention and most of the companies are adopting this new paradigm and gaining significant benefits. As number of applications and business operations are being facilitated by the cloud computing paradigm it has become the potential target to attackers. The importance of well-organized architecture and security roles have become greater with the growing popularity. Cloud Security: Attacks Techniques Tools and Challenges provides an in-depth technical description about various key essential aspects of cloud security. We have endeavored to provide a technical foundation that will be practically useful not just for students and independent researchers but also for professional cloud security analysts for conducting security procedures and all those who are curious in the field of cloud security The book offers comprehensive coverage of the most essential topics including: Basic fundamentals of Cloud Computing Cloud security concepts vulnerabilities security standards and reference models Cloud security goals key issues and privacy requirements Threat model detailed taxonomy of cloud attacks Attack feature analysis – case study A detailed taxonomy of IDS techniques and Cloud Intrusion Detection Systems (IDS) Attack and security tools LibVMI – case study Advanced approaches: Virtual Machine Introspection (VMI) and Hypervisor Introspection (HVI) Container security: threat model attacks and defense systems This book is intended for both academic and professional audience. It could also be used as a textbook for a semester course at undergraduate and post graduate level in Computer Science Information Technology Information Security and Information Science & Management. The book serves as basic reference volume for researchers in cloud security. It will be useful to practitioners cloud security team and the cloud security auditor as well. To get the most out of this book the reader should have a working knowledge of various operating system environments hypervisors cloud computing fundamentals programming languages like Python and a working knowledge of security tools. | Cloud Security Attacks Techniques Tools and Challenges

GBP 130.00
1

Mobile Devices Tools and Technologies

Mobile Devices Tools and Technologies

Wireless and mobile communications have grown exponentially. The average individual now possesses a minimum of two smart mobile devices. The consistent advancement of mobile devices feeds the ever-growing appetite for faster bandwidth uninterrupted connectivity applications to fulfill the needs of consumers and businesses and security for all of this information. Mobile Devices: Tools and Technologies provides readers at all levels of technical expertise with an understanding of mobile device concepts application development processes networking and infrastructure and security methods. This book is organized into four sections with chapters contributed by engineers with extensive real-world experience in the mobile and wireless field. The first section discusses the current mobile device landscape including the latest technology innovations personal and business use trends and mobile operating systems and applications. The second section focuses on the application development process from strategy and process through the development phases to production and launch. This section covers both Android and iOS application development. In the third section the authors explore mobile access standards network types and infrastructure components. This section also covers proximity communications standards including Bluetooth NFC and RFID. The book concludes with a look at mobile device security including mobile encryption methods wireless security levels and corporate security and workforce management strategies. Throughout the book the contributors illustrate proven best practices and methodologies using real-world case studies drawn from their extensive experiences with mobile software and infrastructures for enterprise customers. | Mobile Devices Tools and Technologies

GBP 44.99
1

Big Data and Social Science Data Science Methods and Tools for Research and Practice

Big Data and Social Science Data Science Methods and Tools for Research and Practice

Big Data and Social Science: Data Science Methods and Tools for Research and Practice Second Edition shows how to apply data science to real-world problems covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences statistics and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data apply data science methods and tools to the data and recognize and respond to data errors biases and limitations. Features: Takes an accessible hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data code and practical programming exercises through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner. | Big Data and Social Science Data Science Methods and Tools for Research and Practice

GBP 52.99
1

Advances in Complex Decision Making Using Machine Learning and Tools for Service-Oriented Computing

Advances in Complex Decision Making Using Machine Learning and Tools for Service-Oriented Computing

The rapidly evolving business and technology landscape demands sophisticated decision-making tools to stay ahead of the curve. Advances in Complex Decision Making: Using Machine Learning and Tools for Service-Oriented Computing is a cutting-edge technical guide exploring the latest decision-making technology advancements. This book provides a comprehensive overview of machine learning algorithms and examines their applications in complex decision-making systems in a service-oriented framework. The authors also delve into service-oriented computing and how it can be used to build complex systems that support decision making. Many real-world examples are discussed in this book to provide a practical insight into how discussed techniques can be applied in various domains including distributed computing cloud computing IoT and other online platforms. For researchers students data scientists and technical practitioners this book offers a deep dive into the current developments of machine learning algorithms and their applications in service-oriented computing. This book discusses various topics including Fuzzy Decisions ELICIT OWA aggregation Directed Acyclic Graph RNN LSTM GRU Type-2 Fuzzy Decision Evidential Reasoning algorithm and robust optimisation algorithms. This book is essential for anyone interested in the intersection of machine learning and service computing in complex decision-making systems. | Advances in Complex Decision Making Using Machine Learning and Tools for Service-Oriented Computing

GBP 44.99
1

Moving Shape Analysis and Control Applications to Fluid Structure Interactions

Moving Shape Analysis and Control Applications to Fluid Structure Interactions

Problems involving the evolution of two- and three-dimensional domains arise in many areas of science and engineering. Emphasizing an Eulerian approach Moving Shape Analysis and Control: Applications to Fluid Structure Interactions presents valuable tools for the mathematical analysis of evolving domains. The book illustrates the efficiency of the tools presented through different examples connected to the analysis of noncylindrical partial differential equations (PDEs) such as Navier–Stokes equations for incompressible fluids in moving domains. The authors first provide all of the details of existence and uniqueness of the flow in both strong and weak cases. After establishing several important principles and methods they devote several chapters to demonstrating Eulerian evolution and derivation tools for the control of systems involving fluids and solids. The book concludes with the boundary control of fluid–structure interaction systems followed by helpful appendices that review some of the advanced mathematics used throughout the text. This authoritative resource supplies the computational tools needed to optimize PDEs and investigate the control of complex systems involving a moving boundary. | Moving Shape Analysis and Control Applications to Fluid Structure Interactions

GBP 59.99
1

Optimization Modelling Using R

Optimization Modelling Using R

This book covers using R for doing optimization a key area of operations research which has been applied to virtually every industry. The focus is on linear and mixed integer optimization. It uses an algebraic modeling approach for creating formulations that pairs naturally with an algebraic implementation in R. With the rapid rise of interest in data analytics a data analytics platform is key. Working technology and business professionals need an awareness of the tools and language of data analysis. R reduces the barrier to entry for people to start using data analytics tools. Philosophically the book emphasizes creating formulations before going intoimplementation. Algebraic representation allows for clear understanding and generalizationof large applications and writing formulations is necessary to explain and convey the modeling decisions made. Appendix A introduces R. Mathematics is used at the level of subscripts and summations Refreshers are provided in Appendix B. This book: • Provides and explains code so examples are relatively clear and self-contained. • Emphasizes creating algebraic formulations before implementing. • Focuses on application rather than algorithmic details. • Embodies the philosophy of reproducible research. • Uses open-source tools to ensure access to powerful optimization tools. • Promotes open-source: all materials are available on the author’s github repository. • Demonstrates common debugging practices with a troubleshooting emphasis specific to optimization modeling using R. • Provides code readers can adapt to their own applications. This book can be used for graduate and undergraduate courses for students without a background in optimization and with varying mathematical backgrounds. | Optimization Modelling Using R

GBP 82.99
1

Modeling and Simulation in Python

Modeling and Simulation in Python

The use of Python as a powerful computational tool is expanding with great strides. Python is a language which is easy to use and the libraries of tools provides it with efficient versatility. As the tools continue to expand users can create insightful models and simulations. While the tools offer an easy method to create a pipeline such constructions are not guaranteed to provide correct results. A lot of things can go wrong when building a simulation - deviously so. Users need to understand more than just how to build a process pipeline. Modeling and Simulation in Python introduces fundamental computational modeling techniques that are used in a variety of science and engineering disciplines. It emphasizes algorithmic thinking skills using different computational environments and includes a number of interesting examples including Shakespeare movie databases virus spread and Chess. Key Features: Several theories and applications are provided each with working Python scripts. All Python functions written for this book are archived on GitHub. Readers do not have to be Python experts but a working knowledge of the language is required. Students who want to know more about the foundations of modeling and simulation will find this an educational and foundational resource.

GBP 82.99
1

Analyzing US Census Data Methods Maps and Models in R

Analyzing US Census Data Methods Maps and Models in R

Census data is widely used by practitioners to understand demographic change allocate resources address inequalities and make sound business decisions. Until recently projects using US Census data have required proficiency with multiple web interfaces and software platforms to prepare map and present data products. This book introduces readers to tools in the R programming language for accessing and analyzing Census data and shows how to carry out demographic analyses in a single computing environment. Chapters in this book cover the following key topics: • Rapidly acquiring data from the decennial US Census and American Community Survey using R then analyzing these datasets using tidyverse tools; • Visualizing US Census data with a wide range of methods including charts in ggplot2 as well as both static and interactive maps; • Using R as a geographic information system (GIS) to manage analyze and model spatial demographic data from the US Census; • Working with and modeling individual-level microdata from the American Community Survey’s PUMS datasets; • Applying these tools and workflows to the analysis of historical Census data other US government datasets and international Census data from countries like Canada Brazil Kenya and Mexico. | Analyzing US Census Data Methods Maps and Models in R

GBP 52.99
1

Bioinformatics A Practical Approach

Bioinformatics A Practical Approach

An emerging ever-evolving branch of science bioinformatics has paved the way for the explosive growth in the distribution of biological information to a variety of biological databases including the National Center for Biotechnology Information. For growth to continue in this field biologists must obtain basic computer skills while computer specialists must possess a fundamental understanding of biological problems. Bridging the gap between biology and computer science Bioinformatics: A Practical Approach assimilates current bioinformatics knowledge and tools relevant to the omics age into one cohesive concise and self-contained volume. Written by expert contributors from around the world this practical book presents the most state-of-the-art bioinformatics applications. The first part focuses on genome analysis common DNA analysis tools phylogenetics analysis and SNP and haplotype analysis. After chapters on microarray SAGE regulation of gene expression miRNA and siRNA the book presents widely applied programs and tools in proteome analysis protein sequences protein functions and functional annotation of proteins in murine models. The last part introduces the programming languages used in biology website and database design and the interchange of data between Microsoft Excel and Access. Keeping complex mathematical deductions and jargon to a minimum this accessible book offers both the theoretical underpinnings and practical applications of bioinformatics. | Bioinformatics A Practical Approach

GBP 59.99
1

A Concise Introduction to Robot Programming with ROS2

A Concise Introduction to Robot Programming with ROS2

A Concise Introduction to Robot Programming with ROS2 provides the reader with the concepts and tools necessary to bring a robot to life through programming. It will equip the reader with the skills necessary to undertake projects with ROS2 the new version of ROS. It is not necessary to have previous experience with ROS2 as it will describe its concepts tools and methodologies from the beginning. Key Features Uses the two programming languages officially supported in ROS2 (C++ mainly and Python) Approaches ROS2 from three different but complementary dimensions: the Community Computation Graph and the Workspace Includes a complete simulated robot development and testing strategies Behavior Trees and Nav2 description setup and use A GitHub repository with code to assist readers It will appeal to motivated engineering students engineers and professionals working with robot programming.

GBP 44.99
1

From Computing to Computational Thinking

From Computing to Computational Thinking

Computational Thinking (CT) involves fundamental concepts and reasoning distilled from computer science and other computational sciences which become powerful general mental tools for solving problems increasing efficiency reducing complexity designing procedures or interacting with humans and machines. An easy-to-understand guidebook From Computing to Computational Thinking gives you the tools for understanding and using CT. It does not assume experience or knowledge of programming or of a programming language but explains concepts and methods for CT with clarity and depth. Successful applications in diverse disciplines have shown the power of CT in problem solving. The book uses puzzles games and everyday examples as starting points for discussion and for connecting abstract thinking patterns to real-life situations. It provides an interesting and thought-provoking way to gain general knowledge about modern computing and the concepts and thinking processes underlying modern digital technologies.

GBP 180.00
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

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry academia and government. It introduces the tidyverse suite of R packages including the ggplot2 package for data visualization and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses the book covers traditional introductory statistics topics like confidence intervals hypothesis testing and multiple regression modeling while focusing on visualization throughout. Features: ● Assumes minimal prerequisites notably no prior calculus nor coding experience ● Motivates theory using real-world data including all domestic flights leaving New York City in 2013 the Gapminder project and the data journalism website FiveThirtyEight. com ● Centers on simulation-based approaches to statistical inference rather than mathematical formulas ● Uses the infer package for tidy and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods ● Provides all code and output embedded directly in the text; also available in the online version at moderndive. com This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics at both the undergraduate and graduate levels.

GBP 66.99
1

Handbook of Item Response Theory Three Volume Set

Handbook of Item Response Theory Three Volume Set

Drawing on the work of 75 internationally acclaimed experts in the field Handbook of Item Response Theory Three-Volume Set presents all major item response models classical and modern statistical tools used in item response theory (IRT) and major areas of applications of IRT in educational and psychological testing medical diagnosis of patient-reported outcomes and marketing research. It also covers CRAN packages WinBUGS Bilog MG Multilog Parscale IRTPRO Mplus GLLAMM Latent Gold and numerous other software tools. A full update of editor Wim J. van der Linden and Ronald K. Hambleton’s classic Handbook of Modern Item Response Theory this handbook has been expanded from 28 chapters to 85 chapters in three volumes. The three volumes are thoroughly edited and cross-referenced with uniform notation format and pedagogical principles across all chapters. Each chapter is self-contained and deals with the latest developments in IRT. | Handbook of Item Response Theory Three Volume Set

GBP 140.00
1

Graphical Methods for Data Analysis

Graphical Methods for Data Analysis

This book present graphical methods for analysing data. Some methods are new and some are old some require a computer and others only paper and pencil; but they are all powerful data analysis tools. In many situations a set of data � even a large set- can be adequately analysed through graphical methods alone. In most other situations a few well-chosen graphical displays can significantly enhance numerical statistical analyses. | Graphical Methods for Data Analysis

GBP 205.00
1

Statistics for Finance

Statistics for Finance

Statistics for Finance develops students’ professional skills in statistics with applications in finance. Developed from the authors’ courses at the Technical University of Denmark and Lund University the text bridges the gap between classical rigorous treatments of financial mathematics that rarely connect concepts to data and books on econometrics and time series analysis that do not cover specific problems related to option valuation. The book discusses applications of financial derivatives pertaining to risk assessment and elimination. The authors cover various statistical and mathematical techniques including linear and nonlinear time series analysis stochastic calculus models stochastic differential equations Itō’s formula the Black–Scholes model the generalized method-of-moments and the Kalman filter. They explain how these tools are used to price financial derivatives identify interest rate models value bonds estimate parameters and much more. This textbook will help students understand and manage empirical research in financial engineering. It includes examples of how the statistical tools can be used to improve value-at-risk calculations and other issues. In addition end-of-chapter exercises develop students’ financial reasoning skills.

GBP 44.99
1

Geographic Data Science with Python

Geographic Data Science with Python

This book provides the tools the methods and the theory to meet the challenges of contemporary data science applied to geographic problems and data. In the new world of pervasive large frequent and rapid data there are new opportunities to understand and analyze the role of geography in everyday life. Geographic Data Science with Python introduces a new way of thinking about analysis by using geographical and computational reasoning it shows the reader how to unlock new insights hidden within data. Key Features: ● Showcases the excellent data science environment in Python. ● Provides examples for readers to replicate adapt extend and improve. ● Covers the crucial knowledge needed by geographic data scientists. It presents concepts in a far more geographic way than competing textbooks covering spatial data mapping and spatial statistics whilst covering concepts such as clusters and outliers as geographic concepts. Intended for data scientists GIScientists and geographers the material provided in this book is of interest due to the manner in which it presents geospatial data methods tools and practices in this new field.

GBP 48.99
1

Convex Analysis

Convex Analysis

Convexity is an ancient idea going back to Archimedes. Used sporadically in the mathematical literature over the centuries today it is a flourishing area of research and a mathematical subject in its own right. Convexity is used in optimization theory functional analysis complex analysis and other parts of mathematics. Convex Analysis introduces analytic tools for studying convexity and provides analytical applications of the concept. The book includes a general background on classical geometric theory which allows readers to obtain a glimpse of how modern mathematics is developed and how geometric ideas may be studied analytically. Featuring a user-friendly approach the book contains copious examples and plenty of figures to illustrate the ideas presented. It also includes an appendix with the technical tools needed to understand certain arguments in the book a tale of notation and a thorough glossary to help readers with unfamiliar terms. This book is a definitive introductory text to the concept of convexity in the context of mathematical analysis and a suitable resource for students and faculty alike.

GBP 175.00
1

The Role of Sustainability and Artificial Intelligence in Education Improvement

The Role of Sustainability and Artificial Intelligence in Education Improvement

This book is devoted to the issues faced by universities in the field of distance learning during and after COVID as well as in digitalization times. The book devotes a lot of space to the issues of Web 3. 0 in university e-learning Industry 4. 0 artificial intelligence and digital equity. The aim and scope of this book is to draw a holistic picture of education before and after COVID the psychological effects of COVID in education and using modern technologies application in education taking into consideration aspects of sustainability development Industry 4. 0 and Society 5. 0. The authors also raise the issue of artificial intelligence investigation in learner-instructor interaction. Features: To elaborate the functions of online education and numerous pedagogical strategies based on electronic learning to aid teachers and students with the tools required to succeed in the 21st century via engaging virtual experiences To analyze tools provided by Ed-Tech firms and the effect of digital tools on maintaining the educational process in times of crisis and after pandemic To create a roadmap for higher education institutions and provide tips regarding how to improve the effectiveness of the hybrid learning system To understand e-learning characteristic in the era of Industry 4. 0 and Society 5. 0 and characteristics of the different web generations To use AI applications to improve connections and relationships between students and teachers and in education in the future The book is both scientific and educational. It can be used at the university level and by anyone interested in the topics it covers. | The Role of Sustainability and Artificial Intelligence in Education Improvement

GBP 110.00
1

Benefit-Risk Assessment Methods in Medical Product Development Bridging Qualitative and Quantitative Assessments

Benefit-Risk Assessment Methods in Medical Product Development Bridging Qualitative and Quantitative Assessments

Guides You on the Development and Implementation of B–R EvaluationsBenefit–Risk Assessment Methods in Medical Product Development: Bridging Qualitative and Quantitative Assessments provides general guidance and case studies to aid practitioners in selecting specific benefit–risk (B–R) frameworks and quantitative methods. Leading experts from industry regulatory agencies and academia present practical examples lessons learned and best practices that illustrate how to conduct structured B–R assessment in clinical development and regulatory submission. The first section of the book discusses the role of B–R assessments in medicine development and regulation the need for both a common B–R framework and patient input into B–R decisions and future directions. The second section focuses on legislative and regulatory policy initiatives as well as decisions made at the U. S. FDA’s Center for Devices and Radiological Health. The third section examines key elements of B–R evaluations in a product’s life cycle such as uncertainty evaluation and quantification quantifying patient B–R trade-off preferences ways to identify subgroups with the best B–R profiles and data sources used to assist B–R assessment. The fourth section equips practitioners with tools to conduct B–R evaluations including assessment methodologies a quantitative joint modeling and joint evaluation framework and several visualization tools. The final section presents a rich collection of case studies. With top specialists sharing their in-depth knowledge thought-provoking considerations and practical advice this book offers comprehensive coverage of B–R evaluation methods tools and case studies. It gives practitioners a much-needed toolkit to develop and conduct their own B–R evaluations. | Benefit-Risk Assessment Methods in Medical Product Development Bridging Qualitative and Quantitative Assessments

GBP 44.99
1

Analysis of Variance Design and Regression Linear Modeling for Unbalanced Data Second Edition

Analysis of Variance Design and Regression Linear Modeling for Unbalanced Data Second Edition

Analysis of Variance Design and Regression: Linear Modeling for Unbalanced Data Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data. New to the Second EditionReorganized to focus on unbalanced dataReworked balanced analyses using methods for unbalanced dataIntroductions to nonparametric and lasso regressionIntroductions to general additive and generalized additive modelsExamination of homologous factorsUnbalanced split plot analysesExtensions to generalized linear modelsR Minitab® and SAS code on the author’s websiteThe text can be used in a variety of courses including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data. | Analysis of Variance Design and Regression Linear Modeling for Unbalanced Data Second Edition

GBP 44.99
1

Implementing Reproducible Research

Implementing Reproducible Research

In computational science reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed data must be accessible in a readable format and a platform must be available for widely distributing the data and code. In addition both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts the book discusses the tools practices and dissemination platforms for ensuring reproducibility in computational science. It describes:Computational tools such as Sweave knitr VisTrails Sumatra CDE and the Declaratron systemOpen source practices good programming practices trends in open science and the role of cloud computing in reproducible researchSoftware and methodological platforms including open source software packages RunMyCode platform and open access journalsEach part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www. ImplementingRR. org.

GBP 44.99
1

Data Science in Practice

Data Science in Practice

Data Science in Practice is the ideal introduction to data science. With or without math skills here you get the all-round view that you need for your projects. This book describes how to properly question data in order to unearth the treasure that data can be. You will get to know the relevant analysis methods and will be introduced to the programming language R which is ideally suited for data analysis. Associated tools like notebooks that make data science programming easily accessible are included in this introduction. Because technology alone is not enough this book also deals with problems in project implementation illuminates various fields of application and does not forget to address ethical aspects. Data Science in Practice includes many examples notes on errors decision-making aids and other practical tips. This book is ideal as a complementary text for university students and is a useful learning tool for those moving into more data-related roles. Key Features: Success factors and tools for all project phases Includes application examples for various subject areas Introduces many aspects of Data Science from requirements analysis to data acquisition and visualization

GBP 54.99
1