Data, Graphing, and Statistics Smarts!

Data, Graphing, and Statistics Smarts!

Author: Rebecca Wingard-Nelson

Publisher: Enslow Publishers, Inc.

Published: 2012-09

Total Pages: 66

ISBN-13: 1464503575

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Are you having trouble with graphs? Do you wish someone could explain data, graphing, or statistics to you in a clear, simple way? From ratios and line plots to percentiles and sampling, this book takes a step-by-step approach to teaching data, graphing, and statistics concepts. This book is designed for students to use alone or with a tutor or parent, provides clear lessons with easy-to-learn techniques and plenty of examples. Whether you are looking to learn this information for the first time, on your own or with a tutor, or you would like to review your skills, this book will be a great choice.


Data Smart

Data Smart

Author: John W. Foreman

Publisher: John Wiley & Sons

Published: 2013-10-31

Total Pages: 432

ISBN-13: 1118839862

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Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.


Knowledge Graphs and Big Data Processing

Knowledge Graphs and Big Data Processing

Author: Valentina Janev

Publisher: Springer Nature

Published: 2020-07-15

Total Pages: 212

ISBN-13: 3030531996

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This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.


Big Data and You

Big Data and You

Author: Mindy Mozer

Publisher: The Rosen Publishing Group, Inc

Published: 2014-07-15

Total Pages: 50

ISBN-13: 1477776451

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The collection, organization, and analysis of how people use information technology is commonly referred to as "Big Data." And companies, schools, the government, and other organizations are harnessing it to do their jobs more effectively. This volume is a complete guide to Big Data: what it is, how it is used, and how it will continue to be used. Readers can better understand how Big Data plays a part in their lives today and how it will continue to be an enormous factor in the future.


Smart Data Discovery Using SAS Viya

Smart Data Discovery Using SAS Viya

Author: Felix Liao

Publisher: SAS Institute

Published: 2020-08-11

Total Pages: 206

ISBN-13: 1635267242

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Gain Powerful Insights with SAS Viya! Whether you are an executive, departmental decision maker, or analyst, the need to leverage data and analytical techniques in order make critical business decisions is now crucial to every part of an organization. Smart Data Discovery with SAS Viya: Powerful Techniques for Deeper Insights provides you with the necessary knowledge and skills to conduct a smart discovery process and empower you to ask more complex questions using your data. The book highlights key components of a smart data discovery process utilizing advanced machine learning techniques, powerful capabilities from SAS Viya, and finally brings it all together using real examples and applications. With its step-by-step approach and integrated examples, the book provides a relevant and practical guide to insight discovery that goes beyond traditional charts and graphs. By showcasing the powerful visual modeling capabilities of SAS Viya, it also opens up the world of advanced analytics and machine learning techniques to a much broader set of audiences.


Smart Technologies in Data Science and Communication

Smart Technologies in Data Science and Communication

Author: Kingsley A. Ogudo

Publisher: Springer Nature

Published: 2023-01-01

Total Pages: 317

ISBN-13: 9811968802

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This book features high-quality, peer-reviewed research papers presented at the Fifth International Conference on Smart Technologies in Data Science and Communication (SMARTDSC 2022), held Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India, on 16 – 17 June 2022. It includes innovative and novel contributions in the areas of data analytics, communication and soft computing.


Smart Education and e-Learning 2019

Smart Education and e-Learning 2019

Author: Vladimir L. Uskov

Publisher: Springer

Published: 2019-05-31

Total Pages: 625

ISBN-13: 9811382603

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This book contains the contributions presented at the 6th international KES conference on Smart Education and e-Learning (KES SEEL-2019), which took place at St. Julian’s, Malta, June 17–19, 2019. It contains fifty-five high-quality peer-reviewed papers that are grouped into several interconnected parts: Part 1 – Smart Education, Part 2 – Smart e-Learning, Part 3 – Smart Pedagogy, Part 4 – Smart Education: Systems and Technology, Part 5 – Smart Education: Case Studies and Research, Part 6 – Students with Disabilities and Smart Education/University, and Part 7 – Mathematical Modelling of Smart Education and Economics of Smart University. Smart education and smart e-learning are emerging and rapidly growing areas with the potential to transform existing teaching strategies, learning environments, and educational activities and technology in the classroom. Smart education and smart e-learning focus on enabling instructors to develop new ways of achieving excellence in teaching in highly technological smart classrooms, and providing students with new opportunities to maximize their success and select the best options for their education, location and learning style, as well as the mode of content delivery. This book serves as a useful source of research data and valuable information on current research projects, best practices and case studies for faculty, scholars, Ph.D. students, administrators, and practitioners – all those who are interested in smart education and smart e-learning.


Smart Algorithms: The Power of AI and Machine Learning

Smart Algorithms: The Power of AI and Machine Learning

Author: Dr.S.Gandhimathi

Publisher: SK Research Group of Companies

Published: 2024-06-10

Total Pages: 206

ISBN-13: 819714804X

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Dr.S.Gandhimathi, Assistant Professor, Department of Computer Science, Valluvar College of Science and Management, Karur, Tamil Nadu, India. Dr.K.Sivakami, Associate Professor, Department of Computer Science, Nadar Saraswathi College of Arts and Science, Theni, Tamil Nadu, India. Dr.B.Senthilkumaran, Assistant Professor, Department of Computer Science and Engineering, School of Computing, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai,Tamil Nadu, India. Dr.John T Mesia Dhas, Associate Professor, Department of Computer Science and Engineering, School of Computing, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai,Tamil Nadu, India. Mrs.S.Saranya, Assistant Professor, Department of Computer Science, Valluvar College of Science and Management, Karur, Tamil Nadu, India.


Smart Data

Smart Data

Author: Kuan-Ching Li

Publisher: CRC Press

Published: 2019-03-19

Total Pages: 429

ISBN-13: 0429018037

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Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories, data mining and machine learning techniques. The book features contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning, Big Data capture and representation, AI for Big Data applications, and more. Features Presents state-of-the-art research in big data and smart computing Provides a broad coverage of topics in data science and machine learning Combines computing methods with domain knowledge and a focus on applications in science, engineering, and business Covers data security and privacy, including AI techniques Includes contributions from leading researchers