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Big Data – BigData 2020

Author : Surya Nepal
Publisher : Springer Nature
Page : 264 pages
File Size : 44,30 MB
Release : 2020-09-17
Category : Computers
ISBN : 3030596125

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This book constitutes the proceedings of the 9th International Conference on Big Data, BigData 2020, held as part of SCF 2020, during September 18-20, 2020. The conference was planned to take place in Honolulu, HI, USA and was changed to a virtual format due to the COVID-19 pandemic. The 16 full and 3 short papers presented were carefully reviewed and selected from 52 submissions. The topics covered are Big Data Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc.), Big Data Analytics, Big Data Toolkits, Big Data Open Platforms, Economic Analysis, Big Data for Enterprise Transformation, Big Data in Business Performance Management, Big Data for Business Model Innovations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions.

Big Data

Author : Hong Mei
Publisher : Springer Nature
Page : 261 pages
File Size : 34,24 MB
Release : 2021-03-31
Category : Computers
ISBN : 9811607052

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This book constitutes the proceedings of the 8th CCF Conference on Big Data, BigData 2020, held in Chongqing, China, in October 2020. The 16 full papers presented in this volume were carefully reviewed and selected from 65 submissions. They present recent research on theoretical and technical aspects on big data, as well as on digital economy demands in big data applications.

Big Data

Author :
Publisher :
Page : 261 pages
File Size : 43,77 MB
Release : 2021
Category : Big data
ISBN : 9789811607066

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This book constitutes the proceedings of the 8th CCF Conference on Big Data, BigData 2020, held in Chongqing, China, in October 2020. The 16 full papers presented in this volume were carefully reviewed and selected from 65 submissions. They present recent research on theoretical and technical aspects on big data, as well as on digital economy demands in big data applications.

Big Data – BigData 2021

Author : Jinpeng Wei
Publisher : Springer Nature
Page : 129 pages
File Size : 24,10 MB
Release : 2022-02-15
Category : Computers
ISBN : 3030962822

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This book constitutes the refereed proceedings of the 10th International Conference on Big Data, BigData 2021, held online as part of SCF 2021, during December 10-14, 2021. The 6 full and 2 short papers presented were carefully reviewed and selected from 53 submissions. The topics covered are Big Data Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc.), Big Data Analytics, Big Data Toolkits, Big Data Open Platforms, Economic Analysis, Big Data for Enterprise Transformation, Big Data in Business Performance Management, Big Data for Business Model Innovations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions.

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John MacIntyre
Publisher : Springer Nature
Page : 907 pages
File Size : 41,63 MB
Release : 2020-11-03
Category : Computers
ISBN : 3030627438

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This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Big Data Analytics

Author : Ladjel Bellatreche
Publisher : Springer Nature
Page : 350 pages
File Size : 50,43 MB
Release : 2021-01-02
Category : Computers
ISBN : 3030666654

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This book constitutes the proceedings of the 8th International Conference on Big Data Analytics, BDA 2020, which took place during December 15-18, 2020, in Sonepat, India. The 11 full and 3 short papers included in this volume were carefully reviewed and selected from 48 submissions; the book also contains 4 invited and 3 tutorial papers. The contributions were organized in topical sections named as follows: data science systems; data science architectures; big data analytics in healthcare; information interchange of Web data resources; and business analytics.

Big Data

Author : James Warren
Publisher : Simon and Schuster
Page : 481 pages
File Size : 23,67 MB
Release : 2015-04-29
Category : Computers
ISBN : 1638351104

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Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John MacIntyre
Publisher : Springer Nature
Page : 887 pages
File Size : 16,20 MB
Release : 2020-11-04
Category : Computers
ISBN : 3030627462

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This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Big Data

Author : Anthony S. Williams
Publisher : Anthony S. Williams
Page : 345 pages
File Size : 14,26 MB
Release :
Category : Computers
ISBN :

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Big Data - 4 book BUNDLE!! Data Analytics for Beginners In this book you will learn: Putting Data Analytics to Work The Rise of Data Analytics Big Data Defined Cluster Analysis Applications of Cluster Analysis Commonly Graphed Information Data Visualization Four Important Features of Data Visualization Software Big Data Impact Envisaged by 2020 Pros and Cons of Big Data Analytics And of course much more! Deep Learning with Keras In this book you will learn: Deep Neural Network Neural Network Elements Keras Models Sequential Model Functional API Model Keras Layers Core Keras Layers Convolutional Keras Layers Recurrent Keras Layers Deep Learning Algorithms Supervised Learning Algorithms Applications of Deep Learning Models Automatic Speech and Image Recognition Natural Language Processing Video Game Development Real World Applications And of course much more! Analyzing Data with Power BI In this book you will learn: Basics of data analysis processes Fundamental data analysis algorithms Basic of data and text mining, data visualization and business intelligence Techniques used for analysing quantitative data Basic data analysis tasks Conceptual, logical and physical data models Power BI service and data modelling Creating reports and visualizations in Power BI Data transformation and data cleaning in Power BI Real world applications of data analysis Convolutional Neural Networks In Python In this book you will learn: Architecture of convolutional neural networks Solving computer vision tasks using convolutional neural networks Python and computer vision Automatic image and speech recognition Theano and TenroeFlow image recognition How to use MNIST vision dataset What are commonly used convolutional filters Download this book bundle NOW and SAVE money!!

Big Data Analytics and Knowledge Discovery

Author : Min Song
Publisher : Springer Nature
Page : 413 pages
File Size : 19,9 MB
Release : 2020-09-10
Category : Computers
ISBN : 3030590658

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The volume LNCS 12393 constitutes the papers of the 22nd International Conference Big Data Analytics and Knowledge Discovery which will be held online in September 2020. The 15 full papers presented together with 14 short papers plus 1 position paper in this volume were carefully reviewed and selected from a total of 77 submissions. This volume offers a wide range to following subjects on theoretical and practical aspects of big data analytics and knowledge discovery as a new generation of big data repository, data pre-processing, data mining, text mining, sequences, graph mining, and parallel processing.