Название: Advancement of Data Processing Methods for Artificial and Computing Intelligence
Автор: Sееmа Rаwаt, V. Аjаnthа Dеvi, Рrаvееn Кumаr
Издательство: River Publishers
Серия: River Publishers Series in Computing and Information Science and Technology
Год: 2024
Страниц: 431
Язык: английский
Формат: pdf (true)
Размер: 36.7 MB

This book emphasizes the applications of advances in data processing methods for Artificial Intelligence in today's fast-changing world, as well as to serve society through research, innovation, and development in this field. This book is applicable to a wide range of data that contribute to data science concerns and can be used to promote research in this high-potential new field. People's perceptions of the world and how they conduct their lives have changed dramatically as a result of technological advancements. The world has been gripped by technology, and the advances that are being made every day are undeniably transforming the planet. In the domains of Big Data, engineering, and Data Science, this cutting-edge technology is ready to support us. Artificial Intelligence (AI) is a current research topic because it can be applied to a wide range of applications and disciplines to solve complicated problems and find optimal solutions. In research, medicine, technology, and the social sciences, the benefits of AI have already been proven. Data Science, also known as pattern analytics and mining, is a technique for extracting useful and relevant information from databases, enabling better decision-making and strategy formulation in a range of fields. As a result of the exponential growth of data in recent years, the combined notions of Big Data and AI have given rise to many study areas, such as scale-up behaviour from classical algorithms.

Название: Data Analytics and Adaptive Learning: Research Perspectives
Автор: Patsy D. Moskal, Charles D. Dziuban, Anthony G. Picciano
Издательство: Routledge
Год: 2024
Страниц: 364
Язык: английский
Формат: pdf (true)
Размер: 21.6 MB

Data Analytics and Adaptive Learning offers new insights into the use of emerging data analysis and adaptive techniques in multiple learning settings. In recent years, both analytics and adaptive learning have helped educators become more responsive to learners in virtual, blended, and personalized environments. This set of rich, illuminating, international studies spans quantitative, qualitative, and mixed-methods research in higher education, K–12, and adult/continuing education contexts. By exploring the issues of definition and pedagogical practice that permeate teaching and learning and concluding with recommendations for the future research and practice necessary to support educators at all levels, this book will prepare researchers, developers, and graduate students of instructional technology to produce evidence for the benefits and challenges of data-driven learning.

Название: Data Curious: Applying Agile Analytics for Better Business Decisions (Third Early Release)
Автор: Carl Allchin, Sarah Nooravi
Издательство: O’Reilly Media, Inc.
Год: 2023-06-22
Страниц: 158
Язык: английский
Формат: epub (true), mobi
Размер: 10.1 MB

Citizen data analysts are emerging to fill in the gaps left by traditional and slow business intelligence processes. Business functions such as finance, supply chain, and sales are now leading new data/analytics initiatives rather than partnering with centralized IT or analytics teams. But there is a knowledge gap—these new "citizen data analysts" understand their area of business, but unlike their IT counterparts, they do not have a background in data processing technology.

Название: Be Data Analytical: How to Use Analytics to Turn Data into Value
Автор: Jordan Morrow
Издательство: Kogan Page
Год: 2023
Страниц: 241
Язык: английский
Формат: pdf (true), epub
Размер: 12.98 MB

Be Data Analytical is the book organizations and individuals need to understand how to truly use analytics to turn data into valuable insights and drive smarter decision making. Data needs analytics to turn it into value and for organizations to be truly data-driven, they need to use analytics correctly. However, most organizations do not move beyond the first, most rudimentary stage of analytics. They miss out on the powerful insights and opportunities available with all the four levels of analytics: descriptive, diagnostic, predictive and prescriptive. Be Data Analytical reveals how to supercharge data value through all the four levels of analytics, bringing data to life and enhancing data-driven decision making. Be Data Analytical examines each of these four levels of analytics in-depth: what they are, why they matter, how they can be used strategically and how they can be implemented.

Название: Artificial Intelligence Techniques in Human Resource Management
Автор: Soumi Ghosh, Soumi Majumder, Santosh Kumar Das
Издательство: Apple Academic Press/CRC Press
Год: 2024
Страниц: 281
Язык: английский
Формат: pdf (true)
Размер: 13.6 MB

This new volume presents a range of techniques that aim to enhance the operation of human resource management by applying state-of-the-art Artificial Intelligence (AI) technology. With illustrative case studies, the volume uses examples from several real-life problems and includes their possible solutions using advanced AI technology. The book explores the confluence of smart computing and traditional businesses to foster productivity, profitability, and prosperity and goes on to apply AI techniques in the recruitment process, with enterprise resource planning management software, for manpower optimization systems in colleges, for creating uniformity in HRM across organizations, for creating conflicting strategy management techniques, and more. One pandemicrelated chapter discusses the use of radio frequency-based technology for monitoring social distancing.

Название: Azure Modern Data Architecture : A Guide to Design and Implement a Modern Data Solutions
Автор: Anouar Ben Zahra
Издательство: Leanpub
Год: 2023
Страниц: 319
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Introducing the ultimate guide to building modern data warehouses with Azure! Whether you're new to the field or a seasoned professional, this book is packed with valuable insights, practical tips, and real-world examples. From designing robust data pipelines to implementing scalable analytics solutions. This book presents a guide to design and implement scalable, secure, and efficient data solutions in the Azure cloud environment. It provides Data Architects, developers, and IT professionals who are responsible for designing and implementing data solutions in the Azure cloud environment with the knowledge and tools needed to design and implement data solutions using the latest Azure data services. It covers a wide range of topics, including data storage, data processing, data analysis, and data integration. In this book, you will learn how to select the appropriate Azure data services, design a data processing pipeline, implement real-time data processing, and implement advanced analytics using Azure Databricks and Azure Synapse Analytics. You will also learn how to implement data security and compliance, including data encryption, access control, and auditing.

Название: Navigating Big Data Analytics: Strategies for the Quality Systems Analyst
Автор: William D. Mawby
Издательство: ASQ Quality Press
Год: 2021
Страниц: 198
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

More organizations and their leaders are looking to Big Data to transform processes and elevate the quality of products and services. Yet, gathering and storing large amounts of data isn't the quick fix often sought after. Without analysts-the human component-to interpret that data, the cost of incorrect or misinterpreted data can greatly impact organizations. In this book, William Mawby examines the claims of Big Data analysis in detail. Using examples to illustrate potential problems that may lead to inefficient and inaccurate results, Mawby helps practitioners avoid potential pitfalls and offers application methods to incorporate Big Data analytics into your company that will enhance your analytic efforts. Big data analytics is defined as the use of algorithms on large data sets to drive decisions that are of value to a company or Often the power of a big data analytics approach is emphasized by describing it as having three “V” words: volume, velocity, and variety.

Название: Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications
Автор: Debabrata Samanta, SK Hafzul Islam, Naveen Chilamkurti
Издательство: CRC Press
Год: 2022
Страниц: 275
Язык: английский
Формат: pdf (true), epub (true)
Размер: 15.8 MB

With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for Machine Learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how Machine Learning improves the computational model based on the new information. Numerous programming languages work along with ML involving Python, R, Java, and javascript. Python is the popular choice for many developers because of its Tensor Flow library, which helps to give a comprehensive ecosystem of ML tools.

Название: Intelligent Analytics for Industry 4.0 Applications
Автор: Аvinаsh Сhаndrа Pаndеy, Аbhishеk Vеrmа, Vijаураl Singh Rаthоr
Издательство: CRC Press
Год: 2023
Страниц: 313
Язык: английский
Формат: pdf (true)
Размер: 13.6 MB

The advancements in intelligent decision-making techniques have elevated the efficiency of manufacturing industries and led to the start of the Industry 4.0 era. Industry 4.0 is revolutionizing the way companies manufacture, improve, and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and Artificial Intelligence (AI) and Machine Learning (ML), into their production facilities throughout their operations. In the past few years, intelligent analytics has emerged as a solution that examines both historical and real-time data to uncover performance insights. Because the amount of data that needs analysis is growing daily, advanced technologies are necessary to collect, arrange, and analyze incoming data. This approach enables businesses to detect valuable connections and trends and make decisions that boost overall performance. In Industry 4.0, intelligent analytics has a broader scope in terms of descriptive, predictive, and prescriptive subdomains. To this end, the book will aim to review and highlight the challenges faced by intelligent analytics in Industry 4.0 and present the recent developments done to address those challenges.

Название: Thinking Clearly with data: A Guide to Quantitative Reasoning and Analysis
Автор: Ethan Bueno de Mesquita, Anthony Fowler
Издательство: Princeton University Press
Год: 2021
Страниц: 400
Язык: английский
Формат: pdf, epub
Размер: 10.0 MB

An engaging introduction to Data Science that emphasizes critical thinking over statistical techniques. An introduction to Data Science or statistics shouldn’t involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize. In contrast, Thinking Clearly with Data focuses, first and foremost, on critical thinking and conceptual understanding in order to teach students how to be better consumers and analysts of the kinds of quantitative information and arguments that they will encounter throughout their lives.