Ai Based Data Analytics
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Ai Based Data Analytics
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Author : Kiran Chaudhary
language : en
Publisher: CRC Press
Release Date : 2023-12-29
Ai Based Data Analytics written by Kiran Chaudhary and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-29 with Computers categories.
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. Highlights of the book include: The role of Explainable AI in improving customer experiences in e-commerce Sentiment analysis of social media Data analytics in business intelligence Federated learning for business intelligence AI-based planning of business management An AI-based business model innovation in new technologies An analysis of social media marketing and online impulse buying behaviour AI-Based Data Analytics: Applications for Business Management has two primary focuses. The first is on analytics for decision-making and covers big data analytics for market intelligence, data analytics and consumer behavior, and the role of big data analytics in organizational decision-making. The book’s second focus is on digital marketing and includes the prediction of marketing by consumer analytics, web analytics for digital marketing, smart retailing, and leveraging web analytics for optimizing digital marketing strategies.
Ai Based Approach To Efficient Data Retrieval In Big Data Analytics
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Author : Divya
language : en
Publisher:
Release Date : 2023-05-16
Ai Based Approach To Efficient Data Retrieval In Big Data Analytics written by Divya and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-16 with categories.
Big data analytics involves processing and analyzing large volumes of complex data in order to extract meaningful insights and make data-driven decisions. One of the biggest challenges in big data analytics is retrieving relevant data efficiently, especially as the volume of data grows. An AI-based approach to efficient data retrieval in big data analytics involves using artificial intelligence algorithms and techniques to automate and optimize the process of retrieving relevant data from large data sets. This can help improve the efficiency and accuracy of the data retrieval process, allowing organizations to extract insights from their data more quickly and effectively. One common approach to AI-based data retrieval is to use machine learning algorithms to analyze large data sets and identify patterns and relationships between data points. These algorithms can then be used to predict which data points are likely to be relevant for a particular analysis, allowing the system to retrieve only the most relevant data. Another approach is to use natural language processing (NLP) techniques to analyze unstructured data, such as text documents or social media posts, and extract relevant information. NLP algorithms can be used to identify keywords and phrases that are relevant to a particular analysis, allowing the system to retrieve only the most relevant data. AI-based approaches to efficient data retrieval in big data analytics can help organizations save time and resources, while also improving the accuracy and quality of their analyses. By automating and optimizing the data retrieval process, these solutions can help organizations extract insights from their data more quickly and effectively, enabling them to make data-driven decisions with greater confidence.
Ai Based Predictive Analytics
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Author : Minghai Zheng
language : en
Publisher: Independently Published
Release Date : 2023-06-02
Ai Based Predictive Analytics written by Minghai Zheng and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-02 with categories.
1. #DataDrivenDecisions #PredictiveAnalytics Unlock the power of data-driven decisions with AI-based predictive analytics! This book provides the insights and tools you need to make informed decisions based on data. 2. #AIinBusiness #PredictiveModeling Stay ahead of the competition with AI-based predictive analytics. Learn how to implement predictive modeling in your business with this must-read book. 3. #BigDataInsights #DecisionMaking Want to make better decisions based on big data insights? Look no further than "AI-Based Predictive Analytics." This book is your ultimate guide to leveraging the power of AI for predictive analytics. 4. #MachineLearning #DataAnalysis Discover the latest machine learning techniques for data analysis with "AI-Based Predictive Analytics." This book will help you make sense of complex data sets and turn them into actionable insights. 5. #BusinessIntelligence #AIinAction Maximize your business intelligence capabilities with AI-based predictive analytics. Get your copy of this book to learn how to implement these powerful strategies in your organization. In today's data-driven world, predictive analytics has emerged as a powerful tool for organizations looking to make informed decisions based on data. By analyzing historical data and identifying patterns, predictive analytics enables businesses to predict future outcomes and take proactive measures to improve outcomes. With the rise of artificial intelligence (AI), predictive analytics has become even more sophisticated, offering new ways to analyze data and uncover insights that were previously impossible to obtain. The book "AI-Based Predictive Analytics: Empowering Data-Driven Decisions" provides a comprehensive guide on how to implement AI-based predictive analytics strategies in your organization. Whether you're an analyst, data scientist, or business leader, this book will provide you with practical insights and tools to improve decision-making and drive success. In this book, we'll explore various ways in which AI can be used in predictive analytics. We'll discuss the latest machine learning techniques, including deep learning, natural language processing, and regression analysis. Additionally, we'll examine case studies of successful implementations of AI-based predictive analytics in different industries, along with the benefits and challenges associated with these implementations. Whether you're looking to reduce costs, improve efficiency, or enhance customer experiences, this book will provide you with the knowledge and tools needed to achieve your goals. The chapters that follow will delve deeper into specific topics related to AI-based predictive analytics, providing you with a comprehensive guide for implementing these strategies in your organization. MingHai Zheng is the founder of zhengpublishing.com and lives in Wuhan, China. His main publishing areas are business, management, self-help, computers and other emerging foreword fields.
Artificial Intelligence Trends For Data Analytics Using Machine Learning And Deep Learning Approaches
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Author : K. Gayathri Devi
language : en
Publisher: CRC Press
Release Date : 2020-10-07
Artificial Intelligence Trends For Data Analytics Using Machine Learning And Deep Learning Approaches written by K. Gayathri Devi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-07 with Computers categories.
Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications. Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning
Data Analytics And Ai
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Author : Jay Liebowitz
language : en
Publisher: CRC Press
Release Date : 2020-08-06
Data Analytics And Ai written by Jay Liebowitz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-06 with Computers categories.
Analytics and artificial intelligence (AI), what are they good for? The bandwagon keeps answering, absolutely everything! Analytics and artificial intelligence have captured the attention of everyone from top executives to the person in the street. While these disciplines have a relatively long history, within the last ten or so years they have exploded into corporate business and public consciousness. Organizations have rushed to embrace data-driven decision making. Companies everywhere are turning out products boasting that "artificial intelligence is included." We are indeed living in exciting times. The question we need to ask is, do we really know how to get business value from these exciting tools? Unfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science, artificial intelligence, and autonomy by giving a historical perspective for each of these fields, followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures, as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data.
Applying Data Science
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Author : Arthur K. Kordon
language : en
Publisher: Springer Nature
Release Date : 2020-09-12
Applying Data Science written by Arthur K. Kordon and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-12 with Computers categories.
This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence methods. In Part I, the author introduces a problem-driven approach to implementing AI-based data science and offers practical explanations of key technologies: machine learning, deep learning, decision trees and random forests, evolutionary computation, swarm intelligence, and intelligent agents. In Part II, he describes the main steps in creating AI-based data science solutions for business problems, including problem knowledge acquisition, data preparation, data analysis, model development, and model deployment lifecycle. Finally, in Part III the author illustrates the power of AI-based data science with successful applications in manufacturing and business. He also shows how to introduce this technology in a business setting and guides the reader on how to build the appropriate infrastructure and develop the required skillsets. The book is ideal for data scientists who will implement the proposed methodology and techniques in their projects. It is also intended to help business leaders and entrepreneurs who want to create competitive advantage by using AI-based data science, as well as academics and students looking for an industrial view of this discipline.
Artificial Intelligence Accelerates Human Learning
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Author : Katashi Nagao
language : en
Publisher: Springer
Release Date : 2019-02-02
Artificial Intelligence Accelerates Human Learning written by Katashi Nagao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-02 with Education categories.
Focusing on students’ presentations and discussions in laboratory seminars, this book presents case studies on evidence-based education using artificial intelligence (AI) technologies. It proposes a system to help users complete research activities, and a machine-learning method that makes the system suitable for long-term operation by performing data mining for discussions and automatically extracting essential tasks. By illustrating the complete process – proposal, implementation, and operation – of applying machine learning techniques to real-world situations, the book will inspire researchers and professionals to develop innovative new applications for education. The book is divided into six chapters, the first of which provides an overview of AI research and practice in education. In turn, Chapter 2 describes a mechanism for applying data analytics to student discussions and utilizing the results for knowledge creation activities such as research. Based on discussion data analytics, Chapter 3 describes a creative activity support system that effectively utilizes the analytical results of the discussion for subsequent activities. Chapter 4 discusses the incorporation of a gamification method to evaluate and improve discussion skills while maintaining the motivation to participate in the discussion. Chapters 5 and 6 describe an advanced learning environment for honing students’ discussion and presentation skills. Two important systems proposed here are a presentation training system using virtual reality technologies, and an interactive presentation/discussion training system using a humanoid robot. In the former, the virtual space is constructed by measuring the three-dimensional shape of the actual auditorium, presentations are performed in the same way as in the real world, and the AI as audience automatically evaluates the presentation and provides feedback. In the latter, a humanoid robot makes some remarks on and asks questions about students’ presentations, and the students practice responding to it.
Artificial Intelligence For Business Analytics
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Author : Felix Weber
language : en
Publisher: Springer Nature
Release Date : 2023-03-01
Artificial Intelligence For Business Analytics written by Felix Weber and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-01 with Computers categories.
While methods of artificial intelligence (AI) were until a few years ago exclusively a topic of scientific discussions, today they are increasingly finding their way into products of everyday life. At the same time, the amount of data produced and available is growing due to increasing digitalization, the integration of digital measurement and control systems, and automatic exchange between devices (Internet of Things). In the future, the use of business intelligence (BI) and a look into the past will no longer be sufficient for most companies.Instead, business analytics, i.e., predictive and predictive analyses and automated decisions, will be needed to stay competitive in the future. The use of growing amounts of data is a significant challenge and one of the most important areas of data analysis is represented by artificial intelligence methods.This book provides a concise introduction to the essential aspects of using artificial intelligence methods for business analytics, presents machine learning and the most important algorithms in a comprehensible form using the business analytics technology framework, and shows application scenarios from various industries. In addition, it provides the Business Analytics Model for Artificial Intelligence, a reference procedure model for structuring BA and AI projects in the company. This book is a translation of the original German 1st edition Künstliche Intelligenz für Business Analytics by Felix Weber, published by Springer Fachmedien Wiesbaden GmbH, part of Springer Nature in 2020. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors.
The 7th International Conference Nanotechnology Gtunano
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Author : Levan Chkhartishvili
language : en
Publisher: Trans Tech Publications Ltd
Release Date : 2025-12-03
The 7th International Conference Nanotechnology Gtunano written by Levan Chkhartishvili and has been published by Trans Tech Publications Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-03 with Technology & Engineering categories.
Selected peer-reviewed extended articles based on abstracts presented at the 7th International Conference “Nanotechnology” (GTUnano2024) Aggregated Book
Essential Data Analytics Data Science And Ai
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Author : Maxine Attobrah
language : en
Publisher: Springer Nature
Release Date : 2024-12-18
Essential Data Analytics Data Science And Ai written by Maxine Attobrah and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-18 with Computers categories.
In today’s world, understanding data analytics, data science, and artificial intelligence is not just an advantage but a necessity. This book is your thorough guide to learning these innovative fields, designed to make the learning practical and engaging. The book starts by introducing data analytics, data science, and artificial intelligence. It illustrates real-world applications, and, it addresses the ethical considerations tied to AI. It also explores ways to gain data for practice and real-world scenarios, including the concept of synthetic data. Next, it uncovers Extract, Transform, Load (ETL) processes and explains how to implement them using Python. Further, it covers artificial intelligence and the pivotal role played by machine learning models. It explains feature engineering, the distinction between algorithms and models, and how to harness their power to make predictions. Moving forward, it discusses how to assess machine learning models after their creation, with insights into various evaluation techniques. It emphasizes the crucial aspects of model deployment, including the pros and cons of on-device versus cloud-based solutions. It concludes with real-world examples and encourages embracing AI while dispelling fears, and fostering an appreciation for the transformative potential of these technologies. Whether you’re a beginner or an experienced professional, this book offers valuable insights that will expand your horizons in the world of data and AI. What you will learn: What are Synthetic data and Telemetry data How to analyze data using programming languages like Python and Tableau. What is feature engineering What are the practical Implications of Artificial Intelligence Who this book is for: Data analysts, scientists, and engineers seeking to enhance their skills, explore advanced concepts, and stay up-to-date with ethics. Business leaders and decision-makers across industries are interested in understanding the transformative potential and ethical implications of data analytics and AI in their organizations.