Tag: Data

Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing 10th International Conference, RSFDGrC 2005, Regina, Canada, Augus


Free Download Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 10th International Conference, RSFDGrC 2005, Regina, Canada, August 31 – September 3, 2005, Proceedings, Part I By Zdzisław Pawlak (auth.), Dominik Ślęzak, Guoyin Wang, Marcin Szczuka, Ivo Düntsch, Yiyu Yao (eds.)
2005 | 748 Pages | ISBN: 3540286535 | PDF | 9 MB
This volume contains the papers selected for presentation at the 10th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, organized at the University of Regina, August 31st-September 3rd, 2005. This conference followed in the footsteps of inter- tional events devoted to the subject of rough sets, held so far in Canada, China, Japan,Poland,Sweden, and the USA. RSFDGrC achievedthe status of biennial international conference, starting from 2003 in Chongqing, China. The theory of rough sets, proposed by Zdzis law Pawlak in 1982, is a model of approximate reasoning. The main idea is based on indiscernibility relations that describe indistinguishability of objects. Concepts are represented by – proximations. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to signi?cant results in many areas such as ?nance, industry, multimedia, and medicine. The RSFDGrC conferences put an emphasis on connections between rough sets and fuzzy sets, granularcomputing, and knowledge discoveryand data m- ing, both at the level of theoretical foundations and real-life applications. In the case of this event, additional e?ort was made to establish a linkage towards a broader range of applications. We achieved it by including in the conference program the workshops on bioinformatics, security engineering, and embedded systems, as well as tutorials and sessions related to other application areas.

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Microsoft Certified – Azure Data Engineer Associate 300 practice multiple choice questions and answers


Free Download Microsoft Certified – Azure Data Engineer Associate: 300 practice multiple choice questions and answers by James Howlett
English | August 9, 2024 | ISBN: N/A | ASIN: B0DCT4TD4V | 98 pages | EPUB | 0.13 Mb
Are you ready to take your career to the next level with the Microsoft Certified: Azure Data Engineer Associate certification?

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Journal on Data Semantics VII


Free Download Journal on Data Semantics VII By Yuan An, Alex Borgida, John Mylopoulos (auth.), Stefano Spaccapietra (eds.)
2006 | 267 Pages | ISBN: 3540463291 | PDF | 6 MB
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. Based on the highly visible publication platform Lecture Notes in Computer Science, this new journal is widely disseminated and available worldwide.The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.

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Intelligent Data Engineering and Automated Learning – IDEAL 2005 6th International Conference, Brisbane, Australia, July 6-8,


Free Download Intelligent Data Engineering and Automated Learning – IDEAL 2005: 6th International Conference, Brisbane, Australia, July 6-8, 2005. Proceedings By Juryon Paik, Dongho Won, Farshad Fotouhi, Ung Mo Kim (auth.), Marcus Gallagher, James P. Hogan, Frederic Maire (eds.)
2005 | 600 Pages | ISBN: 354026972X | PDF | 9 MB
This book constitutes the refereed proceedings of the 6th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2005, held in Brisbane, Australia, in July 2005.The 76 revised full papers presented were carefully reviewed and selected from 167 submissions. The papers are organized in topical sections on data mining and knowledge engineering, learning algorithms and systems, bioinformatics, agent technologies, and financial engineering.

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How Teachers Can Turn Data into Action


Free Download Daniel R. Venables, "How Teachers Can Turn Data into Action"
English | ISBN: 1416617582 | 2013 | 149 pages | EPUB | 4 MB
From state and Common Core tests to formative and summative assessments in the classroom, teachers are awash in data. Reviewing the data can be time-consuming, and the work of translating data into real change can seem overwhelming.

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Harnessing Data Science for Sustainable Agriculture and Natural Resource Management


Free Download Harnessing Data Science for Sustainable Agriculture and Natural Resource Management
English | 2024 | ISBN: 9819777615 | 368 Pages | PDF EPUB (True) | 85 MB
This book is a comprehensive resource that handles the issues of sustainable agriculture and natural resource management, aligned with the United Nations’ Sustainable Development Goals (SDGs). The book is organized into five sections, Understanding the Problem, Data Collection and Cleaning, Exploratory Data Analysis and Visualization, Model Building, and Model Deployment. Each section covers a critical aspect of data science in this context and addresses specific SDGs 2-zero hunger, 6-clean water and sanitation, 12-responsible consumption and production, 13-climate action, and 15-Life on land. The organized sections are arranged to seamlessly follow the data science pipeline and provide practical guidance from problem understanding to its model deployment and stakeholder management. The book is useful for researchers, students, practitioners, and policymakers.

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Frame Theory in Data Science (Advances in Science, Technology & Innovation)


Free Download Frame Theory in Data Science (Advances in Science, Technology & Innovation) by Zhihua Zhang, Palle E. T. Jorgensen
English | April 11, 2024 | ISBN: 3031494822 | 263 pages | MOBI | 97 Mb
This book establishes brand-new frame theory and technical implementation in data science, with a special focus on spatial-scale feature extraction, network dynamics, object-oriented analysis, data-driven environmental prediction, and climate diagnosis. Given that data science is unanimously recognized as a core driver for achieving Sustainable Development Goals of the United Nations, these frame techniques bring fundamental changes to multi-channel data mining systems and support the development of digital Earth platforms. This book integrates the authors’ frame research in the past twenty years and provides cutting-edge techniques and depth for scientists, professionals, and graduate students in data science, applied mathematics, environmental science, and geoscience.

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Deep Learning for Seismic Data Enhancement and Representation


Free Download Deep Learning for Seismic Data Enhancement and Representation
English | 2024 | ISBN: 3031757440 | 287 Pages | PDF EPUB (True) | 182 MB
Seismic imaging is a key component of subsurface exploration, and it depends on a high-quality seismic data acquisition system with effective seismic processing algorithms. Seismic data quality concerns various factors such as acquisition design, environmental constraints, sampling resolution, and noises. The focus of this book is to investigate efficient seismic data representation and signal enhancement solutions by leveraging the powerful feature engineering capability of deep learning.

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Databricks Certified Data Engineer Associate Study Guide (Early Release)


Free Download Databricks Certified Data Engineer Associate Study Guide (Early Release)
English | 2024 | ISBN: 9781098166823 | 75 pages | MOBI | 3.95 Mb
Data engineers proficient in Databricks are currently in high demand. As organizations gather more data than ever before, skilled data engineers on platforms like Databricks become critical to business success. The Databricks Data Engineer Associate certification is proof that you have a complete understanding of the Databricks platform and its capabilities, as well as the essential skills to effectively execute various data engineering tasks on the platform.

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