Название: Data Analytics and Machine Learning: Navigating the Big Data Landscape Автор: Рushра Singh, Аshа Rаni Мishrа, Рауаl Gаrg Издательство: Springer Серия: Studies in Big Data Год: 2024 Страниц: 357 Язык: английский Формат: pdf (true) Размер: 10.7 MB This book presents an in-depth analysis of successful data-driven initiatives, highlighting how organizations have leveraged data to drive decision-making processes, optimize operations, and achieve remarkable outcomes. Through case studies, readers gain valuable insights and learn practical strategies for implementing data analytics, Big Data, and Machine Learning solutions in their own organizations. The book discusses the transformative power of data analytics and Big Data in various industries and sectors and how Machine Learning applications have revolutionized exploration by enabling advanced data analysis techniques for mapping, geospatial analysis, and environmental monitoring, enhancing our understanding of the world and its dynamic processes. This book explores how Big Data explosion, the power of analytics and Machine Learning revolution can bring new prospects and opportunities in the dynamic and data-rich landscape. It highlights the future research directions in data analytics, Big Data, and Machine Learning that explores the emerging trends, challenges, and opportunities in these fields by covering interdisciplinary approaches such as handling and analyzing real-time and streaming data. The study is done using a popular statistical tool named R programming.
Название: Industry 4.0 Convergence with AI, IoT, Big Data and Cloud Computing: Fundamentals, Challenges and Applications Автор: Раrikshit N. Маhаllе, Gitаnjаli R. Shindе, Рrасhi М. Jоshi Издательство: Bentham Science Publishers Серия: IoT and Big Data Analytics (Volume 4) Год: 2023 Страниц: 196 Язык: английский Формат: pdf (true), epub Размер: 32.1 MB This volume showcases upcoming trends and applications that are set to redefine our technological landscape. Chapters comprise referenced reviews focused on the recent research that introduces new methods and techniques for using AI in Industry 4.0, and the integration of Internet of Things (IoT) to drive new industrial processes. The contributors have discussed challenges in industry 4.0 along with the applications and the way it is shaping different industries. Key themes: AI in Communication Media: Uncover the latest research, with insights into the challenges and adoption of AI in remote processes. New AI Techniques for Industry 4.0: Learn about technologies such as blockchains and applications of machine learning, deep learning, and image processing. IoT and AI for Smart Systems: Understand IoT with a special focus on enhancing smart systems, in different industries, including agriculture and transaction processing Explorable AI: Gain a quick understanding of Explainable AI (XAI) and its role in improving the predictability and transparency of IoT applications. Whether you're a tech enthusiast, researcher, or industry professional, this book offers a glimpse into the innovative world of Industry 4.0 and its intersection with AI, IoT, Big Data, and cloud computing.
Название: Big Data Management and Analytics Автор: Вrij В Guрtа and Маmtа Издательство: World Scientific Publishing Год: 2024 Страниц: 288 Язык: английский Формат: pdf (true) Размер: 19.6 MB With the proliferation of information, Big Data management and analysis have become an indispensable part of any system to handle such amounts of data. The amount of data generated by the multitude of interconnected devices increases exponentially, making the storage and processing of these data a real challenge. Big Data management and analytics have gained momentum in almost every industry, ranging from finance or healthcare. Big Data can reveal key insights if handled and analyzed properly; it has great application potential to improve the working of any industry. This book covers the spectrum aspects of Big Data; from the preliminary level to specific case studies. It will help readers gain knowledge of the Big Data landscape.Highlights of the topics covered include description of the Big Data ecosystem; real-world instances of Big Data issues; how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reporting; structural process to get value out of Big Data and recognize the differences between a standard database management system and a Big Data management system. Readers will gain insights into choice of data models, data extraction, data integration to solve large data problems, data modelling using Machine Learning techniques, Spark's scalable Machine Learning techniques, modeling a Big Data problem into a graph database and performing scalable analytical operations over the graph and different tools and techniques for processing Big Data and its applications including in healthcare and finance.
Название: Big Data and Hadoop: Fundamentals, tools, and techniques for data-driven success - 2nd Edition Автор: Мауаnk Вhushаn Издательство: BPB Publications Год: 2024 Страниц: 548 Язык: английский Формат: epub (true) Размер: 27.8 MB In today's data-driven world, harnessing the power of big data is no longer a luxury, but a necessity. This comprehensive guide, "Big Data and Hadoop," dives deep into the world of big data and equips you with the knowledge and skills you need to conquer even the most complex data landscapes. Start with the fundamentals of big data, exploring its growing significance and diverse applications. You'll look into the heart of the Apache Hadoop ecosystem, mastering its core components like HDFS and MapReduce. We'll demystify NoSQL databases, introducing you to HBase and Cassandra as powerful alternatives to traditional databases. Clarify the details of MapReduce programming with practical examples, and discover the power of PigLatin and HiveQL for efficient data analysis. Explore advanced tools like Spark, unlocking its potential for real-time data processing and analytics. Rounding out your knowledge, the book delves into practical applications, exploring real-world scenarios and research-based insights. By the end of this book, you'll emerge as a confident big data explorer, equipped to tackle any data challenge with expertise and precision. Whether you are a beginner or have some experience with Big Data. This book is for aspiring Big Data professionals, including data analysts, software developers, IT professionals, and students in Computer Science and related fields.
Название: Hypothesis Generation and Interpretation: Design Principles and Patterns for Big Data Applications Автор: Нirоshi Ishikаwа Издательство: Springer Серия: Studies in Big Data Год: 2024 Страниц: 380 Язык: английский Формат: pdf (true) Размер: 11.1 MB This book focuses in detail on Data Science and data analysis and emphasizes the importance of data engineering and data management in the design of Big Data applications. The author uses patterns discovered in a collection of Big Data applications to provide design principles for hypothesis generation, integrating Big Data processing and management, Machine Learning and data mining techniques. The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on “social infrastructure” applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases. The novel methods and technologies proposed in Hypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns. In the Big Data era, characterized by volume, variety, and velocity, which generates a large amount of diverse data at high speed, the role of a hypothesis is more important to generate the final value, and such a hypothesis is more complicated and complex than ever. At the same time, the era of Big Data creates new vague concerns for end users as to whether Big Data relevant to them will be used appropriately.
Название: Smart Cities: IoT Technologies, Big Data Solutions, Cloud Platforms, and Cybersecurity Techniques Автор: Аlех Кhаng, Shаshi Каnt Guрtа, Sitа Rаni Издательство: CRC Press Год: 2024 Страниц: 429 Язык: английский Формат: pdf (true) Размер: 21.3 MB This book discusses the basic principles of sustainable development in a smart city ecosystem to better serve the life of citizens. It examines smart city systems driven by emerging IoT-powered technologies and the other dependent platforms. This book is based on the design and implementation of Internet of Things (IoT), Artificial Intelligence (AI), Data Science, Big Data solutions, cloud platforms, cyber-security technology, and emerging technologies in the smart city ecosystem. Smart Cities: AI, IoT Technologies, Big Data Solutions, Cloud Platforms, and Cybersecurity Techniques discusses the design and implementation of the core components of the smart city ecosystem. The editors discuss the effective management and development of smart city infrastructures, starting with planning and integrating complex models and diverse frameworks into an ecosystem. Specifically the chapters examine the core infrastructure elements, including activities of the public and private services as well as innovative ICT solutions, computer vision, IoT technologies, data tools, cloud services, AR/VR technologies, cybersecurity techniques, treatment solution of the environmental water pollution, and other intelligent devices for supporting sustainable living in the smart environment.
Название: Big Data Computing: Advances in Technologies, Methodologies, and Applications Автор: Таnvir Наbib Sаrdаr, Вishwаjееt Кumаr Раndеу Издательство: CRC Press Серия: Computational Intelligence Techniques Год: 2024 Страниц: 397 Язык: английский Формат: pdf (true) Размер: 15.0 MB This book primarily aims to provide an in-depth understanding of recent advances in Big Data computing technologies, methodologies, and applications along with introductory details of Big Data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and Big Data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in Big Data computing applications such as Machine Learning, Deep Learning, graph processing, and many others. Big Data has become a critical issue for businesses to leverage their data assets to drive business decisions considering the exponential growth of data in today’s age. Machine Learning (ML) and Artificial Intelligence (AI) have emerged as powerful tools to extract insights and value from Big Data. Here we will explore a few of the key applications of ML and AI in Big Data. Predictive analytics is one of the most significant applications of ML in Big Data. It involves using existing data to predict future events or behaviors. Predictive analytics may be used to predict future sales, identify customers at risk of churning, or predict the likelihood of a customer purchasing a specific product . In predictive analytics, algorithms such as decision trees, random forests, and neural networks are commonly used.
Название: AI-Based Data Analytics: Applications for Business Management Автор: Кirаn Сhаudhаrу, Маnsаf Аlаm Издательство: CRC Press Год: 2024 Страниц: 261 Язык: английский Формат: pdf (true) Размер: 13.6 MB This book covers various topics related to marketing and business analytics. It explores how organizations can increase their profits by making better decisions in a timely manner through the use of data analytics. This book is meant for students, practitioners, industry professionals, researchers, and academics working in the field of commerce and marketing, Big Data analytics, and organizational decision-making. This book is focused on Artificial Intelligence (AI), Data Analytics, Sentiment Analysis for social media, and various approaches to AI in Business Management. This is an emerging field that can increase the performance management domain to improve understanding of business and marketing dynamics that can lead to better strategic decision-making. In this book, we have also given a variety of marketing and business analytics strategies to solve market and organizational challenges. The use of AI in business and marketing analytics can help to create value by proper allocation of all available resources. By using various techniques and tools of Big Data analytics, we can improve the performance of the business. Data analytics is a vast discipline that encompasses a variety of methodologies and technologies. Predictive analytics, data mining, Machine Learning (ML), and Natural Language Processing (NLP) are included.
Название: Critical Data Literacies: Rethinking Data and Everyday Life Автор: Luсi Раngrаziо, Nеil Sеlwуn Издательство: The MIT Press Год: 2023 Страниц: 216 Язык: английский Формат: pdf, azw3, epub (true), mobi Размер: 10.2 MB A guide to everything you need to understand to navigate a world increasingly governed by data. Data has become a defining issue of current times. Our everyday lives are shaped by the data that is produced about us (and by us) through digital technologies. In this book, Critical Data Literacies, Luci Pangrazio and Neil Selwyn introduce readers to the central concepts, ideas, and arguments required to make sense of life in the data age. The authors challenge the idea that datafication is an inevitable and inescapable condition. Drawing on emerging areas of scholarship such as data justice, data feminism, and other critical data studies approaches, they explore how individuals and communities can empower themselves to engage with data critically and creatively. Over the course of eight wide-ranging chapters, the book introduces readers to the main components of critical data literacies—from the fundamentals of identifying and understanding data to the complexities of engaging with more combative data tactics. Critical Data Literacies explores how the tradition of critical literacies can offer a powerful foundation to address the big concerns of the data age, such as issues of data justice and privacy, algorithmic bias, dataveillance, and disinformation.
Название: Google Cloud Platform for Data Science: A Crash Course on Big Data, Machine Learning, and Data Analytics Services Автор: Shitаlkumаr R. Sukhdеvе, Sаndika S. Sukhdеvе Издательство: Apress Год: 2024 Страниц: 231 Язык: английский Формат: pdf Размер: 10.2 MB This book is your practical and comprehensive guide to learning Google Cloud Platform (GCP) for Data Science, using only the free tier services offered by the platform. Data Science and Machine Learning are increasingly becoming critical to businesses of all sizes, and the cloud provides a powerful platform for these applications. GCP offers a range of Data Science services that can be used to store, process, and analyze large datasets, and train and deploy Machine Learning models. The book is organized into seven chapters covering various topics such as GCP account setup, Google Colaboratory, Big Data and Machine Learning, Data Visualization and Business Intelligence, Data Processing and Transformation, Data Analytics and Storage, and Advanced Topics. Each chapter provides step-by-step instructions and examples illustrating how to use GCP services for Data Science and Big Data projects. Readers will learn how to set up a Google Colaboratory account and run Jupyter notebooks, access GCP services and data from Colaboratory, use BigQuery for data analytics, and deploy Machine Learning models using Vertex AI. For Data scientists, machine learning engineers, and analysts who want to learn how to use Google Cloud Platform (GCP) for their Data Science and Big Data projects.
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