Advances In Machine Learning And Big Data Analytics Ii
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Advances In Machine Learning And Big Data Analytics Ii
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Author : Ashokkumar Patel
language : en
Publisher: Springer
Release Date : 2024-06-20
Advances In Machine Learning And Big Data Analytics Ii written by Ashokkumar Patel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-20 with Mathematics categories.
In the dynamic landscape of technology, machine learning and big data analytics have emerged as transformative forces, reshaping industries and empowering innovation. Machine learning, a subset of artificial intelligence, equips systems to learn and adapt from data, revolutionizing decision-making, automation, and predictive capabilities. Meanwhile, Big Data Analytics processes and extracts insights from vast and complex datasets, unveiling hidden patterns and trends. Together, these fields enable us to harness the immense power of data for smarter business strategies, improved healthcare, enhanced user experiences, and countless other applications. This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2023, which was held on May 29-30, 2023 by NERIST and NIT Arunachal Pradesh India) introduces an exciting journey into the intersection of machine learning and Big Data Analytics, where data becomes a catalyst for progress and transformation.
Applications Of Machine Learning In Big Data Analytics And Cloud Computing
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Author : Subhendu Kumar Pani
language : en
Publisher: CRC Press
Release Date : 2022-09-01
Applications Of Machine Learning In Big Data Analytics And Cloud Computing written by Subhendu Kumar Pani and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-01 with Computers categories.
Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.
Deep Learning In Data Analytics
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Author : Debi Prasanna Acharjya
language : en
Publisher: Springer Nature
Release Date : 2021-08-11
Deep Learning In Data Analytics written by Debi Prasanna Acharjya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-11 with Technology & Engineering categories.
This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book's material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.
Business Intelligenceand And Big Data Analytics Ii
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Author : Mr. Rohit Manglik
language : en
Publisher: EduGorilla Publication
Release Date : 2024-07-10
Business Intelligenceand And Big Data Analytics Ii written by Mr. Rohit Manglik and has been published by EduGorilla Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-10 with Computers categories.
EduGorilla Publication is a trusted name in the education sector, committed to empowering learners with high-quality study materials and resources. Specializing in competitive exams and academic support, EduGorilla provides comprehensive and well-structured content tailored to meet the needs of students across various streams and levels.
Advances On Intelligent Computing And Data Science Ii
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Author : Faisal Saeed
language : en
Publisher: Springer Nature
Release Date : 2025-08-22
Advances On Intelligent Computing And Data Science Ii written by Faisal Saeed and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-22 with Computers categories.
This book presents the proceedings of the 4th International Conference on Advanced Computing and Informatics (ICACIn’24). The conference, held on December 16–17, 2024, at STEAMhouse, Birmingham City University (UK), with a parallel session at Hassan II University (Morocco), attracted submissions by researchers in 20 countries. Out of 91 submissions, 46 high-quality papers were selected, presenting the latest advancements and cutting-edge developments in computing and informatics. The book covers a wide range of advanced computing topics, including data science, big data analytics, the Internet of Things (IoT), smart computing, artificial intelligence, machine learning, cybersecurity, intelligent communication systems, health informatics, and information systems. Designed for researchers, practitioners, and graduate students, this book serves as a valuable resource for exploring advanced intelligent computing techniques and their real-world applications.
Big Data Analytics Systems Algorithms Applications
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Author : C.S.R. Prabhu
language : en
Publisher: Springer Nature
Release Date : 2019-10-14
Big Data Analytics Systems Algorithms Applications written by C.S.R. Prabhu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-14 with Computers categories.
This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.
Big Data
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Author : Balamurugan Balusamy
language : en
Publisher: John Wiley & Sons
Release Date : 2021-03-15
Big Data written by Balamurugan Balusamy and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-15 with Mathematics categories.
Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.
Data Analytics And Big Data
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Author : Soraya Sedkaoui
language : en
Publisher: John Wiley & Sons
Release Date : 2018-05-24
Data Analytics And Big Data written by Soraya Sedkaoui and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-24 with Computers categories.
The main purpose of this book is to investigate, explore and describe approaches and methods to facilitate data understanding through analytics solutions based on its principles, concepts and applications. But analyzing data is also about involving the use of software. For this, and in order to cover some aspect of data analytics, this book uses software (Excel, SPSS, Python, etc) which can help readers to better understand the analytics process in simple terms and supporting useful methods in its application.
The International Conference On Advanced Machine Learning Technologies And Applications Amlta2018
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer
Release Date : 2018-01-25
The International Conference On Advanced Machine Learning Technologies And Applications Amlta2018 written by Aboul Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-25 with Technology & Engineering categories.
This book presents the refereed proceedings of the third International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2018, held in Cairo, Egypt, on February 22–24, 2018, and organized by the Scientific Research Group in Egypt (SRGE). The papers cover current research in machine learning, big data, Internet of Things, biomedical engineering, fuzzy logic, security, and intelligence swarms and optimization.
Apache Spark 2 X Machine Learning Cookbook
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Author : Siamak Amirghodsi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-09-22
Apache Spark 2 X Machine Learning Cookbook written by Siamak Amirghodsi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-22 with Computers categories.
Simplify machine learning model implementations with Spark About This Book Solve the day-to-day problems of data science with Spark This unique cookbook consists of exciting and intuitive numerical recipes Optimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your data Who This Book Is For This book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark. A solid knowledge of machine learning algorithms is assumed, as well as hands-on experience of implementing ML algorithms with Scala. However, you do not need to be acquainted with the Spark ML libraries and ecosystem. What You Will Learn Get to know how Scala and Spark go hand-in-hand for developers when developing ML systems with Spark Build a recommendation engine that scales with Spark Find out how to build unsupervised clustering systems to classify data in Spark Build machine learning systems with the Decision Tree and Ensemble models in Spark Deal with the curse of high-dimensionality in big data using Spark Implement Text analytics for Search Engines in Spark Streaming Machine Learning System implementation using Spark In Detail Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization. Learning about algorithms enables a wide range of applications, from everyday tasks such as product recommendations and spam filtering to cutting edge applications such as self-driving cars and personalized medicine. You will gain hands-on experience of applying these principles using Apache Spark, a resilient cluster computing system well suited for large-scale machine learning tasks. This book begins with a quick overview of setting up the necessary IDEs to facilitate the execution of code examples that will be covered in various chapters. It also highlights some key issues developers face while working with machine learning algorithms on the Spark platform. We progress by uncovering the various Spark APIs and the implementation of ML algorithms with developing classification systems, recommendation engines, text analytics, clustering, and learning systems. Toward the final chapters, we'll focus on building high-end applications and explain various unsupervised methodologies and challenges to tackle when implementing with big data ML systems. Style and approach This book is packed with intuitive recipes supported with line-by-line explanations to help you understand how to optimize your work flow and resolve problems when working with complex data modeling tasks and predictive algorithms. This is a valuable resource for data scientists and those working on large scale data projects.