9 results (0,14437 seconds)

Show all filters

Brand

Merchant

Price (EUR)

Reset filter

Products
From
Shops

Explorations in Computing An Introduction to Computer Science and Python Programming

Explorations in Computing An Introduction to Computer Science and Python Programming

An Active Learning Approach to Teaching the Main Ideas in Computing Explorations in Computing: An Introduction to Computer Science and Python Programming teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. Tbook gives beginning students an introduction to computer science concepts and computer programming. Designed for CS0 and CS1 courses it is very well suited for alternative lecture styles including flipped classrooms. Prepares Students for Advanced Work in Computer ScienceA revised and updated version of the author’s Explorations in Computing: An Introduction to Computer Science this text incorporates two major differences. It now uses Python instead of Ruby as the lab software so that students can seamlessly transition from introductory projects to more advanced studies in later courses. The book also introduces Python programming providing students with sufficient programming skills so they can implement their own programs. Practical Step-by-Step ProjectsThe interactive lab projects in each chapter allow students to examine important ideas in computer science particularly how algorithms offer computational solutions to problems. Students can type expressions view results and run experiments that help them understand the concepts in a hands-on way. Web ResourcesThe Python software modules for each lab project are available on the author’s website. The modules include data files and sample Python code that students can copy and modify. In addition the site provides a lab manual of installation instructions and tips for editing programs and running commands in a terminal emulator. | Explorations in Computing An Introduction to Computer Science and Python Programming

GBP 46.99
1

Translational Medicine Strategies and Statistical Methods

Translational Medicine Strategies and Statistical Methods

Examines Critical Decisions for Transitioning Lab Science to a Clinical SettingThe development of therapeutic pharmaceutical compounds is becoming more expensive and the success rates for getting such treatments approved for marketing and to the patients is decreasing. As a result translational medicine (TM) is becoming increasingly important in the healthcare industry – a means of maximizing the consideration and use of information collected as compounds transition from initial lab discovery through pre-clinical testing early clinical trials and late confirmatory studies that lead to regulatory approval of drug release to patients. Translational Medicine: Strategies and Statistical Methods suggests a process for transitioning from the initial lab discovery to the patient’s bedside with minimal disconnect and offers a comprehensive review of statistical design and methodology commonly employed in this bench-to-bedside research. Documents Alternative Research Approaches for Faster and More Accurate Data Judgment CallsElaborating on how to introduce TM into clinical studies this authoritative work presents a keen approach to building executing and validating statistical models that consider data from various phases of development. It also delineates a truly translational example to help bolster understanding of discussed concepts. This comprehensive guide effectively demonstrates how to overcome obstacles related to successful TM practice. It contains invaluable information for pharmaceutical scientists research executives clinicians and biostatisticians looking to expedite successful implementation of this important process. | Translational Medicine Strategies and Statistical Methods

GBP 59.99
1

Exploring Linear Algebra Labs and Projects with MATLAB

Exploring Linear Algebra Labs and Projects with MATLAB

Exploring Linear Algebra: Labs and Projects with MATLAB® is a hands-on lab manual that can be used by students and instructors in classrooms every day to guide the exploration of the theory and applications of linear algebra. For the most part labs discussed in the book can be used individually or in a sequence. Each lab consists of an explanation of material with integrated exercises. Some labs are split into multiple subsections and thus exercises are separated by those subsections. The exercise sections integrate problems using Mathematica demonstrations (an online tool that can be used with a browser with Java capabilities) and MATLAB® coding. This allows students to discover the theory and applications of linear algebra in a meaningful and memorable way. Features: The book’s inquiry-based approach promotes student interaction Each chapter contains a project set which consists of application-driven projects emphasizing the chapter’s materials Adds a project component to any Linear Algebra course Explores many applications to a variety of fields that can promote research projects Employs MATLAB® to calculate and explore concepts and theories of linear algebra | Exploring Linear Algebra Labs and Projects with MATLAB®

GBP 44.99
1

DNA Methylation Microarrays Experimental Design and Statistical Analysis

DNA Methylation Microarrays Experimental Design and Statistical Analysis

Providing an interface between dry-bench bioinformaticians and wet-lab biologists DNA Methylation Microarrays: Experimental Design and Statistical Analysis presents the statistical methods and tools to analyze high-throughput epigenomic data in particular DNA methylation microarray data. Since these microarrays share the same underlying principles as gene expression microarrays many of the analyses in the text also apply to microarray-based gene expression and histone modification (ChIP-on-chip) studies. After introducing basic statistics the book describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systematic artifacts resulting from measurement imperfections. It then explores differential methylation and genomic tiling arrays. Focusing on exploratory data analysis the next several chapters show how cluster and network analyses can link the functions and roles of unannotated DNA elements with known ones. The book concludes by surveying the open source software (R and Bioconductor) public databases and other online resources available for microarray research. Requiring only limited knowledge of statistics and programming this book helps readers gain a solid understanding of the methodological foundations of DNA microarray analysis. | DNA Methylation Microarrays Experimental Design and Statistical Analysis

GBP 59.99
1

Real World AI Ethics for Data Scientists Practical Case Studies

Real World AI Ethics for Data Scientists Practical Case Studies

In the midst of the fourth industrial revolution big data is weighed in gold placing enormous power in the hands of data scientists – the modern AI alchemists. But great power comes with greater responsibility. This book seeks to shape in a practical diverse and inclusive way the ethical compass of those entrusted with big data. Being practical this book provides seven real-world case studies dealing with big data abuse. These cases span a range of topics from the statistical manipulation of research in the Cornell food lab through the Facebook user data abuse done by Cambridge Analytica to the abuse of farm animals by AI in a chapter co-authored by renowned philosophers Peter Singer and Yip Fai Tse. Diverse and inclusive given the global nature of this revolution this book provides case-by-case commentary on the cases by scholars representing non-Western ethical approaches (Buddhist Jewish Indigenous and African) as well as Western approaches (consequentialism deontology and virtue). We hope this book will be a lighthouse for those debating ethical dilemmas in this challenging and ever-evolving field. | Real World AI Ethics for Data Scientists Practical Case Studies

GBP 42.99
1

Information Technology An Introduction for Today’s Digital World

Information Technology An Introduction for Today’s Digital World

This revised edition has more breadth and depth of coverage than the first edition. Information Technology: An Introduction for Today’s Digital World introduces undergraduate students to a wide variety of concepts that they will encounter throughout their IT studies and careers. The features of this edition include: Introductory system administration coverage of Windows 10 and Linux (Red Hat 7) both as general concepts and with specific hands-on instruction Coverage of programming and shell scripting demonstrated through example code in several popular languages Updated information on modern IT careers Computer networks including more content on cloud computing Improved coverage of computer security Ancillary material that includes a lab manual for hands-on exercises Suitable for any introductory IT course this classroom-tested text presents many of the topics recommended by the ACM Special Interest Group on IT Education (SIGITE). It offers a far more detailed examination of the computer and IT fields than computer literacy texts focusing on concepts essential to all IT professionals – from system administration to scripting to computer organization. Four chapters are dedicated to the Windows and Linux operating systems so that students can gain hands-on experience with operating systems that they will deal with in the real world. | Information Technology An Introduction for Today’s Digital World

GBP 74.99
1

Unmatched 50 Years of Supercomputing

Unmatched 50 Years of Supercomputing

Unmatched: 50 Years of Supercomputing: A Personal Journey Accompanying the Evolution of a Powerful Tool The rapid and extraordinary progress of supercomputing over the past half-century is a powerful demonstration of our relentless drive to understand and shape the world around us. In this book David Barkai offers a unique and compelling account of this remarkable technological journey drawing from his own rich experiences working at the forefront of high-performance computing (HPC). This book is a journey delineated as five decade-long ‘epochs’ defined by the systems’ architectural themes: vector processors multi-processors microprocessors clusters and accelerators and cloud computing. The final part examines key issues of HPC and discusses where it might be headed. A central goal of this book is to show how computing power has been applied and more importantly how it has impacted and benefitted society. To this end the use of HPC is illustrated in a range of industries and applications from weather and climate modeling to engineering and life sciences. As such this book appeals to both students and general readers with an interest in HPC as well as industry professionals looking to revolutionize their practice. From the Foreword: “David Barkai's career has spanned five decades during which he has had the rare opportunity to be part of some of the most significant developments in the field of supercomputing. His personal and professional insights combined with his deep knowledge and passion for the subject matter make this book an invaluable resource for anyone interested in the evolution of HPC and its impact on our lives. ” -Horst Simon Director Abu Dhabi Investment Authority (ADIA) Lab | Unmatched 50 Years of Supercomputing

GBP 45.99
1

Linear Algebra and Its Applications with R

Linear Algebra and Its Applications with R

This book developed from the need to teach a linear algebra course to students focused on data science and bioinformatics programs. These students tend not to realize the importance of linear algebra in applied sciences since traditional linear algebra courses tend to cover mathematical contexts but not the computational aspect of linear algebra or its applications to data science and bioinformatics. The author presents the topics in a traditional course yet offers lectures as well as lab exercises on simulated and empirical data sets. This textbook provides students a theoretical basis which can then be applied to the practical R and Python problems providing the tools needed for real-world applications. Each section starts with working examples to demonstrate how tools from linear algebra can help solve problems in applied sciences. These exercises start from easy computations such as computing determinants of matrices to practical applications on simulated and empirical data sets with R so that students learn how to get started with R along with computational examples in each section and then students learn how to apply what they've learned to problems in applied sciences. This book is designed from first principles to demonstrate the importance of linear algebra through working computational examples with R and Python including tutorials on how to install R in the Appendix. If a student has never seen R they can get started without any additional help. Since Python is one of the most popular languages in data science optimization and computer science code supplements are available for students who feel more comfortable with Python. R is used primarily for computational examples to develop students’ practical computational skills. About the Author: Dr. Ruriko Yoshida is an Associate Professor of Operations Research at the Naval Postgraduate School. She received her PhD in Mathematics from the University of California Davis. Her research topics cover a wide variety of areas: applications of algebraic combinatorics to statistical problems such as statistical learning on non-Euclidean spaces sensor networks phylogenetics and phylogenomics. She teaches courses in statistics stochastic models probability and data science. | Linear Algebra and Its Applications with R

GBP 82.99
1

Learn R As a Language

Learn R As a Language

Learning a computer language like R can be either frustrating fun or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward on overcoming them. This book is designed so that it includes smaller and bigger challenges in what I call playgrounds in the hope that all readers will enjoy their path to R fluency. Fluency in the use of a language is a skill that is acquired through practice and exploration. Although rarely mentioned separately fluency in a computer programming language involves both writing and reading. The parallels between natural and computer languages are many but differences are also important. For students and professionals in the biological sciences humanities and many applied fields recognizing the parallels between R and natural languages should help them feel at home with R. The approach I use is similar to that of a travel guide encouraging exploration and describing the available alternatives and how to reach them. The intention is to guide the reader through the R landscape of 2020 and beyond. Features R as it is currently used Few prescriptive rules—mostly the author’s preferences together with alternatives Explanation of the R grammar emphasizing the R way of doing things Tutoring for programming in the small using scripts The grammar of graphics and the grammar of data described as grammars Examples of data exchange between R and the foreign world using common file formats Coaching for becoming an independent R user capable of both writing original code and solving future challenges What makes this book different from others: Tries to break the ice and help readers from all disciplines feel at home with R Does not make assumptions about what the reader will use R for Attempts to do only one thing well: guide readers into becoming fluent in the R language Pedro J. Aphalo is a PhD graduate from the University of Edinburgh and is currently a lecturer at the University of Helsinki. A plant biologist and agriculture scientist with a passion for data electronics computers and photography in addition to plants Dr. Aphalo has been a user of R for 25 years. He first organized an R course for MSc students 18 years ago and is the author of 13 R packages currently in CRAN. | Learn R As a Language

GBP 56.99
1