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Data Science with Java: Practical Methods for Scientists and Engineers, Brzustowicz Michael R.


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Цена: 7602.00р.
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Автор: Brzustowicz Michael R.
Название:  Data Science with Java: Practical Methods for Scientists and Engineers
ISBN: 9781491934111
Издательство: Wiley
Классификация:

ISBN-10: 1491934115
Обложка/Формат: Paperback
Страницы: 300
Вес: 0.41 кг.
Дата издания: 25.04.2016
Язык: English
Иллюстрации: Illustrations, black and white
Размер: 236 x 179 x 15
Читательская аудитория: Professional & vocational
Подзаголовок: Practical methods for scientists and engineers
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание:

A good data scientist knows how to do something really well, but a great data scientist can do something of everything. From raw data all the way to shining in front of C-level executives, a great data scientist has the skills to architect data systems, build applications, perform modeling and machine learning and wrap up the results in a clear (and quickly iterable) manner. From data models to ETL to databases to distributed algorithms and learning, this book has you covered.

While many resources for Java (and data science) exist, none of them combine the two, and especially not at a level where sophisticated concepts are demonstrated clearly and in simplest terms. Data Science with Java marries the two in a practical way.

  • Learn an extremely practical set of tools for creating enterprise grade data science applications
  • Get past the intimidating barrier to machine learning and statistics--and learn how useful object-oriented code can be



Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.

Автор: Witten, Ian H.
Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.
ISBN: 0128042915 ISBN-13(EAN): 9780128042915
Издательство: Elsevier Science
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Цена: 9262.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

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
Making Sense of Data II - A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications

Автор: Myatt
Название: Making Sense of Data II - A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications
ISBN: 0470222808 ISBN-13(EAN): 9780470222805
Издательство: Wiley
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Цена: 14248.00 р.
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Описание: This book provides a general end-to-end discussion concerning the process of translating raw data to scientific and business decisions. The reader`s ability to find patterns in data will be greatly enhanced due to the book`s combination of statistical learning with powerful visualization techniques.

Data Mining: Practical Machine Learning Tools and Techniques,

Автор: Ian H. Witten
Название: Data Mining: Practical Machine Learning Tools and Techniques,
ISBN: 0123748569 ISBN-13(EAN): 9780123748560
Издательство: Elsevier Science
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Цена: 8695.00 р.
Наличие на складе: Поставка под заказ.

Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>

Practical Data Structures and Algorithms with JavaScript

Автор: McMillan Michael
Название: Practical Data Structures and Algorithms with JavaScript
ISBN: 1449364934 ISBN-13(EAN): 9781449364939
Издательство: Wiley
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Цена: 5067.00 р.
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Описание: This practical guide shows you how to work hands-on with a variety of storage mechanisms - including linked lists, stacks, queues, and graphs - within the constraints of the JavaScript environment.

Python and Matplotlib Essentials for Scientists and Engineers

Автор: Matt A. Wood
Название: Python and Matplotlib Essentials for Scientists and Engineers
ISBN: 1681749106 ISBN-13(EAN): 9781681749105
Издательство: Mare Nostrum (Eurospan)
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Цена: 6237.00 р.
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Описание: This book provides an introduction to the core features of the Python programming language and Matplotlib plotting routings for scientists and engineers (or students of either discipline) who want to use Python™ to analyse data, simulate physical processes, and render publication-quality plots. No previous programming experience is needed before reading the first page.Readers will learn the core features of the Python programming language in under a day. They will be able to immediately use Python to implement codes that solve their own problems and make beautiful plots and animations. Python code is extremely fast to prototype, allowing users to achieve results quickly and accurately. The examples within the book are available for download.Python and Matplotlib Essentials for Scientists and Engineers is accessible for motivated high-school students, but will likely be most useful for undergraduate and graduate students as well as working professionals who have some background with the basic mathematical concepts. This book is intended for technical people who want to get things done.

Matrix Methods in Data Mining and Pattern Recognition

Автор: Lars Eld?n
Название: Matrix Methods in Data Mining and Pattern Recognition
ISBN: 0898716268 ISBN-13(EAN): 9780898716269
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed include classification of handwritten digits, text mining, text summarization, pagerank computations related to the Google search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.

Practical ajax projects with java technology

Автор: Zammetti, Frank
Название: Practical ajax projects with java technology
ISBN: 1590596951 ISBN-13(EAN): 9781590596951
Издательство: Springer
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Цена: 6008.00 р.
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Описание: This book will save Java developers countless hours of development time by providing seven complete Ajax applications to learn from and adapt for use in their own projects. The book also details the set-up of a perfect Java/Ajax development environment in which to construct the applications;

JSON at Work: Practical Data Integration for the Web

Автор: Marrs Tom
Название: JSON at Work: Practical Data Integration for the Web
ISBN: 1449358322 ISBN-13(EAN): 9781449358327
Издательство: Wiley
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Цена: 6334.00 р.
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Описание: With this hands-on guide, author and architect Tom Marrs shows you how to build enterprise-class applications and services by leveraging JSON tooling and message/document design.

Practical Data Science

Автор: Andreas Fran?ois Vermeulen
Название: Practical Data Science
ISBN: 1484230531 ISBN-13(EAN): 9781484230534
Издательство: Springer
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Цена: 5309.00 р.
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Описание: Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets.
The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions.

What You'll Learn

  • Become fluent in the essential concepts and terminology of data science and data engineering
  • Build and use a technology stack that meets industry criteria
  • Master the methods for retrieving actionable business knowledge
  • Coordinate the handling of polyglot data types in a data lake for repeatable results
Who This Book Is For

Data scientists and data engineers who are required to convert data from a data lake into actionable knowledge for their business, and students who aspire to be data scientists and data engineers

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