Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications, Srinivasa K. G., Siddesh G. M., Manisekhar S. R.
Описание: Just as people change, so too does fashion. That s why it s so important to recognize newer teaching methods that will help you keep up with fashion trends and the ever-changing world of style. This latest edition of Fashion Design Course helps aspiring fashion designers learn about:
How the digital age impacts education and the design process from research right through to the finished product
Customer Profiles: demographics, psychographics, the role of advertising, and more
Creating a unique vision with help from ethnographic research, design considerations, iconic films and their impact on fashion design, and developing a fabric story
Cultivating your design collection through process and investigation while using Mood Boards, Garment Construction, and more
Producing your own collections with individual exercises based on frequently used concepts for building collections including Shipping Reports, Ethnic Backgrounds, 3D/2D, Concept to Runway, Shifts in Fashion, Accessories, and more
Strategies and tips that will help you transition from coursework to a career in fashion including tips on resumes, interviewing, portfolio presentation, and more
This updated book reflects the latest information in fashion design and development and is an ideal introduction for students, dressmakers, and anyone interested in the creative side of the fashion industry. Discover the new talent, new avenues of inspiration, and new outcomes that are now possible with a degree in fashion design.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Set yourself up for success with this must-have oral radiography text. Dental Radiography: Principles and Techniques gives you a comprehensive foundation for the safe, effective use of radiation in the modern dental office. This combination textbook and training manual features easy-to-understand content combined with step-by-step techniques and a stellar art program to help you apply what you've learned to practice. Plus, new content focuses on pediatrics and the latest in digital and three-dimensional technology
Comprehensive coverage
offers all the information you need to know to prepare for board exams.
Step-by-step procedures help ensure technique mastery and serve as a valuable reference tool.
Technique Tips help you to recognize and prevent the most common performance pitfalls.
Quiz questions provide valuable self-assessment of important concepts.
Key terminology is highlighted in chapter discussions and defined in a back-of-book glossary.
Learning objectives and chapter summaries serve as goal-setting study tools.
EXPANDED Content
on pediatrics/adolescents, digital imaging, and three-dimensional radiography ensures that you're prepared to practice in the modern dental office.
UPDATED Art program depicts the newest technology and equipment and includes new illustrations of anatomy and technique.
UNIQUE Helpful Hint boxes isolate challenging material and offer tips to aid your understanding.
NEW Laboratory Manual provides workbook-style questions and activities to reinforce concepts and step-by-step instructions for in-clinic experiences.
UNIQUE Chapter on three-dimensional imaging helps you to prepare to enter private practice.
UNIQUE Full-color presentation helps you comprehend complex content.
Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Описание: This book tackles some modern trends and methods in the modelling of extreme data. Usually such data arise from random phenomena such as floods, hurricanes, air and water pollutants, extreme claim sizes, life spans, and maximum sizes of ecological populations.
Автор: Lee T. Ostrom, Cheryl A. Wilhelmsen Название: Risk Assessment: Tools, Techniques, and Their Applications ISBN: 1119483468 ISBN-13(EAN): 9781119483465 Издательство: Wiley Рейтинг: Цена: 17733.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Guides the reader through a risk assessment and shows them the proper tools to be used at the various steps in the process
This brand new edition of one of the most authoritative books on risk assessment adds ten new chapters to its pages to keep readers up to date with the changes in the types of risk that individuals, businesses, and governments are being exposed to today. It leads readers through a risk assessment and shows them the proper tools to be used at various steps in the process. The book also provides readers with a toolbox of techniques that can be used to aid them in analyzing conceptual designs, completed designs, procedures, and operational risk.
Risk Assessment: Tools, Techniques, and Their Applications, Second Edition includes expanded case studies and real life examples; coverage on risk assessment software like SAPPHIRE and RAVEN; and end-of-chapter questions for students. Chapters progress from the concept of risk, through the simple risk assessment techniques, and into the more complex techniques. In addition to discussing the techniques, this book presents them in a form that the readers can readily adapt to their particular situation. Each chapter, where applicable, presents the technique discussed in that chapter and demonstrates how it is used.
Expands on case studies and real world examples, so that the reader can see complete examples that demonstrate how each of the techniques can be used in analyzing a range of scenarios
Includes 10 new chapters, including Bayesian and Monte Carlo Analyses; Hazard and Operability (HAZOP) Analysis; Threat Assessment Techniques; Cyber Risk Assessment; High Risk Technologies; Enterprise Risk Management Techniques
Adds end-of-chapter questions for students, and provides a solutions manual for academic adopters
Acts as a practical toolkit that can accompany the practitioner as they perform a risk assessment and allows the reader to identify the right assessment for their situation
Presents risk assessment techniques in a form that the readers can readily adapt to their particular situation
Risk Assessment: Tools, Techniques, and Their Applications, Second Edition is an important book for professionals that make risk-based decisions for their companies in various industries, including the insurance industry, loss control, forensics, all domains of safety, engineering and technical fields, management science, and decision analysis. It is also an excellent standalone textbook for a risk assessment or a risk management course.
Описание: Symmetrical Analysis Techniques for Genetic Systems and Bioinformatics: Advanced Patterns and Applications compiles studies that demonstrate effective approaches to the structural analysis of genetic systems and bioinformatics.
Автор: Mandoiu Название: Bioinformatics Algorithms: Techniques and Applications ISBN: 0470097736 ISBN-13(EAN): 9780470097731 Издательство: Wiley Рейтинг: Цена: 24227.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Bioinformatics Algorithms: Techniques and Applications targets the future collaboration of researchers in algorithms, bioinformatics, and molecular biology. It addresses critical bioinformatics research areas of protein-protein interaction, molecular modeling in drug design, and structural biology.
Автор: Koller Daphne, Friedman Nir Название: Probabilistic Graphical Models: Principles and Techniques ISBN: 0262013193 ISBN-13(EAN): 9780262013192 Издательство: MIT Press Рейтинг: Цена: 21161.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.
Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.
Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.
As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.
Here are just a dozen of the many questions answered within these pages:
What does quantitative analysis of a system really mean?
What is a system?
What are big data and analystics?
How do you know your numbers are good?
What will the future data science environment look like?
How do you determine data provenance?
How do you gather and process information, and then organize, store, and synthesize it?
How does an organization implement data analytics?
Do you really need to think like a Chief Information Officer?
What is the best way to protect data?
What makes a good dashboard?
What is the relationship between eating ice cream and getting attacked by a shark?
The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).
Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.
Автор: Gilbert MacKenzie; Defen Peng Название: Statistical Modelling in Biostatistics and Bioinformatics ISBN: 3319045784 ISBN-13(EAN): 9783319045788 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling.
Автор: Gilbert MacKenzie; Defen Peng Название: Statistical Modelling in Biostatistics and Bioinformatics ISBN: 3319357646 ISBN-13(EAN): 9783319357645 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling.
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