Transparent Data Mining for Big and Small Data, Cerquitelli Tania, Quercia Daniele, Pasquale Frank
Автор: Cerquitelli, Tania, Quercia, Daniele, Pasquale, Frank (Eds.) Название: Transparent data mining for big and small data. ISBN: 3319540238 ISBN-13(EAN): 9783319540238 Издательство: Springer Рейтинг: Цена: 14635.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions.
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
Описание: Getting numbers is easy; getting trustworthy numbers is hard. From experimentation leaders at Amazon, Google, LinkedIn, and Microsoft, this guide to accelerating innovation using A/B tests includes practical examples, pitfalls, and advice for students and industry professionals, plus deeper dives into advanced topics for experienced practitioners.
Название: Handbook of IoT and Big Data ISBN: 1138584207 ISBN-13(EAN): 9781138584204 Издательство: Taylor&Francis Рейтинг: Цена: 29858.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This multi-contributed handbook will contain chapters covering IoT and Big Data, as well as case studies. The book will play a key role for the reader to understand the current scenario and growing paradigm.
Описание: This book, Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don`t, presents you with a step-by-step approach to Data Science as well as secrets only known by the best Data Scientists.
Автор: Esposito Anna, Esposito Antonietta M., Jain Lakhmi C. Название: Innovations in Big Data Mining and Embedded Knowledge ISBN: 3030159418 ISBN-13(EAN): 9783030159412 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Designing a Recommender System for Touristic Activities in a Big Data as a Service Platform.- A Scalable, Transparent Meta-Learning Paradigm for Big Data Applications.- Towards Addressing the Limitations of Educational Policy based on International Large-scale Assessment Data with Castoriadean Magmas.- What do Prospective Students Want? An Observational Study of Preferences About Subject of Study in Higher Education.- Speech Pause Patterns in Collaborative Dialogs.
Автор: Jourdan Название: Metaheuristics for Big Data ISBN: 1848218060 ISBN-13(EAN): 9781848218062 Издательство: Wiley Рейтинг: Цена: 22010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Big Data is a new field, with many technological challenges to be understood in order to use it to its full potential. These challenges arise at all stages of working with Big Data, beginning with data generation and acquisition.
Автор: Schmarzo Bill Название: Big Data MBA ISBN: 1119181119 ISBN-13(EAN): 9781119181118 Издательство: Wiley Рейтинг: Цена: 5069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage.
Автор: Kudyba, Stephan Название: Big Data, Mining, and Analytics ISBN: 0367378817 ISBN-13(EAN): 9780367378813 Издательство: Taylor&Francis Рейтинг: Цена: 9492.00 р. Наличие на складе: Нет в наличии.
Описание:
There is an ongoing data explosion transpiring that will make previous creations, collections, and storage of data look trivial. Big Data, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can leverage them to extract valuable insights from their data. Facilitating a clear understanding of big data, it supplies authoritative insights from expert contributors into leveraging data resources, including big data, to improve decision making.
Illustrating basic approaches of business intelligence to the more complex methods of data and text mining, the book guides readers through the process of extracting valuable knowledge from the varieties of data currently being generated in the brick and mortar and internet environments. It considers the broad spectrum of analytics approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining.
Includes a foreword by Thomas H. Davenport, Distinguished Professor, Babson College; Fellow, MIT Center for Digital Business; and Co-Founder, International Institute for Analytics
Introduces text mining and the transforming of unstructured data into useful information
Examines real time wireless medical data acquisition for today's healthcare and data mining challenges
Presents the contributions of big data experts from academia and industry, including SAS
Highlights the most exciting emerging technologies for big data
Filled with examples that illustrate the value of analytics throughout, the book outlines a conceptual framework for data modeling that can help you immediately improve your own analytics and decision-making processes. It also provides in-depth coverage of analyzing unstructured data with text mining methods.
Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data.
The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.
Автор: Ying Tan; Hideyuki Takagi; Yuhui Shi Название: Data Mining and Big Data ISBN: 331961844X ISBN-13(EAN): 9783319618449 Издательство: Springer Рейтинг: Цена: 9756.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the Second International Conference on Data Mining and Big Data, DMBD 2017, held in Fukuoka, Japan, in July/August 2017. They were organized in topical sections named: association analysis; big data; data analysis; data mining;
Автор: Anna Esposito; Antonietta M. Esposito; Lakhmi C. J Название: Innovations in Big Data Mining and Embedded Knowledge ISBN: 3030159388 ISBN-13(EAN): 9783030159382 Издательство: Springer Рейтинг: Цена: 17074.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the usefulness of knowledge discovery through data mining. With this aim, contributors from different fields propose concrete problems and applications showing how data mining and discovering embedded knowledge from raw data can be beneficial to social organizations, domestic spheres, and ICT markets.Data mining or knowledge discovery in databases (KDD) has received increasing interest due to its focus on transforming large amounts of data into novel, valid, useful, and structured knowledge by detecting concealed patterns and relationships.The concept of knowledge is broad and speculative and has promoted epistemological debates in western philosophies. The intensified interest in knowledge management and data mining stems from the difficulty in identifying computational models able to approximate human behaviors and abilities in resolving organizational, social, and physical problems. Current ICT interfaces are not yet adequately advanced to support and simulate the abilities of physicians, teachers, assistants or housekeepers in domestic spheres. And unlike in industrial contexts where abilities are routinely applied, the domestic world is continuously changing and unpredictable. There are challenging questions in this field: Can knowledge locked in conventions, rules of conduct, common sense, ethics, emotions, laws, cultures, and experiences be mined from data? Is it acceptable for automatic systems displaying emotional behaviors to govern complex interactions based solely on the mining of large volumes of data?Discussing multidisciplinary themes, the book proposes computational models able to approximate, to a certain degree, human behaviors and abilities in resolving organizational, social, and physical problems.The innovations presented are of primary importance for:a. The academic research communityb. The ICT marketc. Ph.D. students and early stage researchersd. Schools, hospitals, rehabilitation and assisted-living centerse. Representatives from multimedia industries and standardization bodies
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