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Advanced Analytics with Spark: Patterns for Learning from Data at Scale, Ryza Sandy, Laserson Uri, Owen Sean


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Цена: 7602.00р.
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Автор: Ryza Sandy, Laserson Uri, Owen Sean
Название:  Advanced Analytics with Spark: Patterns for Learning from Data at Scale
ISBN: 9781491972953
Издательство: Wiley
Классификация:

ISBN-10: 1491972955
Обложка/Формат: Paperback
Страницы: 330
Вес: 0.67 кг.
Дата издания: 25.06.2017
Язык: English
Издание: 2 rev ed
Размер: 244 x 234 x 16
Читательская аудитория: Professional & vocational
Подзаголовок: Patterns for learning from data at scale
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: In the second edition of this practical book, five Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world datasets together to teach you how to approach analytics problems by example.


      Новое издание
Advanced analytics with pyspark

Автор: Tandon, Akash Ryza, Sandy Laserson, Uri Owen, Sean Wills, Josh
Название: Advanced analytics with pyspark
ISBN: 1098103653 ISBN-13(EAN): 9781098103651
Издательство: Неизвестно
Цена: 8394.00 р.
Наличие на складе: Есть у поставщикаПоставка под заказ.
Описание: Updated for Spark 3.0, this practical guide brings together Spark, statistical methods, and real-world datasets to teach you how to approach analytics problems using PySpark, Spark`s Python API, and other best practices in Spark programming.


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.
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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
Learning Analytics

Автор: Johann Ari Larusson; Brandon White
Название: Learning Analytics
ISBN: 1493944401 ISBN-13(EAN): 9781493944408
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This book offers a comprehensive review of Learning Analytics (LA). It highlights the latest results, methodologies, tools, strategies, and models and encompasses theoretical discussions as well as practical examples and strategies.

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>

Statistical and Machine-Learning Data Mining

Автор: Ratner Bruce
Название: Statistical and Machine-Learning Data Mining
ISBN: 1439860912 ISBN-13(EAN): 9781439860915
Издательство: Taylor&Francis
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Цена: 9033.00 р.
Наличие на складе: Поставка под заказ.

Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.

Data Analytics and Learning: Proceedings of Dal 2018

Автор: Nagabhushan P., Guru D. S., Shekar B. H.
Название: Data Analytics and Learning: Proceedings of Dal 2018
ISBN: 9811325138 ISBN-13(EAN): 9789811325137
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book presents new theories and working models in the area of data analytics and learning. The papers included in this volume were presented at the first International Conference on Data Analytics and Learning (DAL 2018), which was hosted by the Department of Studies in Computer Science, University of Mysore, India on 30–31 March 2018. The areas covered include pattern recognition, image processing, deep learning, computer vision, data analytics, machine learning, artificial intelligence, and intelligent systems. As such, the book offers a valuable resource for researchers and practitioners alike.

Handbook of Data Mining and Learning Analytics

Автор: ElAtia Samira
Название: Handbook of Data Mining and Learning Analytics
ISBN: 1118998235 ISBN-13(EAN): 9781118998236
Издательство: Wiley
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Цена: 17258.00 р.
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Описание: Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates.

Recent Developments in Machine Learning and Data Analytics

Автор: Kalita
Название: Recent Developments in Machine Learning and Data Analytics
ISBN: 9811312796 ISBN-13(EAN): 9789811312793
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book presents high-quality papers from an international forum for research on computational approaches to learning. Further, it features work that shows how to apply learning methods to solve important application problems as well as how machine learning research is conducted.

Agile Data Science: Building Full-Stack Data Analytics Applications with Spark

Название: Agile Data Science: Building Full-Stack Data Analytics Applications with Spark
ISBN: 1491960116 ISBN-13(EAN): 9781491960110
Издательство: Wiley
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Цена: 7602.00 р.
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Описание: With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools.

Mastering Azure Analytics: Architecting in the Cloud with Azure Data Lake, Hdinsight, and Spark

Автор: Tejada Zoiner
Название: Mastering Azure Analytics: Architecting in the Cloud with Azure Data Lake, Hdinsight, and Spark
ISBN: 1491956658 ISBN-13(EAN): 9781491956656
Издательство: Wiley
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Цена: 5701.00 р.
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Описание: This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution.

Big data analytics with spark

Автор: Guller, Mohammed
Название: Big data analytics with spark
ISBN: 1484209656 ISBN-13(EAN): 9781484209653
Издательство: Springer
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Цена: 5309.00 р.
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Описание: Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis.

Predictive Analytics with Microsoft Azure Machine Learning 2nd Edition

Автор: Valentine Fontama; Roger Barga; Wee Hyong Tok
Название: Predictive Analytics with Microsoft Azure Machine Learning 2nd Edition
ISBN: 1484212010 ISBN-13(EAN): 9781484212011
Издательство: Springer
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Цена: 6288.00 р.
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Описание: Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models.

Learning Analytics in R with SNA, LSA, and MPIA

Автор: Fridolin Wild
Название: Learning Analytics in R with SNA, LSA, and MPIA
ISBN: 3319287893 ISBN-13(EAN): 9783319287898
Издательство: Springer
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Цена: 13275.00 р.
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Описание: This book introduces Meaningful Purposive Interaction Analysis (MPIA) theory, which combines social network analysis (SNA) with latent semantic analysis (LSA) to help create and analyse a meaningful learning landscape from the digital traces left by a learning community in the co-construction of knowledge.


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