Download or read book Data Centric Artificial Intelligence A Beginner s Guide written by Parikshit N. Mahalle and published by Springer Nature. This book was released on 2023-11-11 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry.

Download or read book Data Centric Artificial Intelligence for Multidisciplinary Applications written by Parikshit N Mahalle and published by CRC Press. This book was released on 2024-06-06 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the need for a data‐centric AI approach and its application in the multidisciplinary domain, compared to a model‐centric approach. It examines the methodologies for data‐centric approaches, the use of data‐centric approaches in different domains, the need for edge AI and how it differs from cloud‐based AI. It discusses the new category of AI technology, "data‐centric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding machine learning and big data analytics tools, data‐centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods. • Includes a collection of case studies with experimentation results to adhere to the practical approaches • Examines challenges in dataset generation, synthetic datasets, analysis, and prediction algorithms in stochastic ways • Discusses methodologies to achieve accurate results by improving the quality of data • Comprises cases in healthcare and agriculture with implementation and impact of quality data in building AI applications

Download or read book Artificial Intelligence and Machine Learning for Business written by Steven Finlay and published by Relativistic. This book was released on 2018-07 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) and Machine Learning are now mainstream business tools. They are being applied across many industries to increase profits, reduce costs, save lives and improve customer experiences. Organizations which understand these tools and know how to use them are benefiting at the expense of their rivals. Artificial Intelligence and Machine Learning for Business cuts through the hype and technical jargon that is often associated with these subjects. It delivers a simple and concise introduction for managers and business people. The focus is very much on practical application and how to work with technical specialists (data scientists) to maximize the benefits of these technologies. This third edition has been substantially revised and updated. It contains several new chapters and covers a broader set of topics than before, but retains the no-nonsense style of the original.

Download or read book A Beginner s Guide to Introduce Artificial Intelligence in Teaching and Learning written by Muralidhar Kurni and published by Springer Nature. This book was released on 2023-06-28 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reimagines education in today’s Artificial Intelligence (AI) world and the Fourth Industrial Revolution. Artificial intelligence will drastically affect every industry and sector, and education is no exception. This book aims at how AI may impact the teaching and learning process in education. This book is designed to demystify AI for teachers and learners. This book will help improve education and support institutions in the phenomena of the emergence of AI in teaching and learning. This book presents a comprehensive study of how AI improves teaching and learning, from AI-based learning platforms to AI-assisted proctored examinations. This book provides educators, learners, and administrators on how AI makes sense in their everyday practice. Describing the application of AI in ten key aspects, this comprehensive volume prepares educational leaders, designers, researchers, and policymakers to effectively rethink the teaching and learning process and environments that students need to thrive. The readers of this book never fall behind the fast pace and promising innovations of today’s most advanced learning technology.

Download or read book Human Centric Computing in a Data Driven Society written by David Kreps and published by Springer Nature. This book was released on 2020-11-11 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th IFIP TC 9 International Conference on Human Choice and Computers, HCC14 2020, which was supposed take place in Tokyo, Japan, in September 2020, but the conference was cancelled due to the COVID-19 crisis. The 31 revised full papers presented were carefully reviewed and selected from 55 submissions. The papers deal with the constantly evolving intimate relationship between humans and technology. They are organized in the following sections: ethical and legal considerations in a data-driven society; the data-driven society; peace and war; our digital lives; individuals in data-driven society; and gender, diversity and ICT.

Download or read book Advances in Financial Machine Learning written by Marcos Lopez de Prado and published by John Wiley & Sons. This book was released on 2018-01-23 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to understand and implement the latest machine learning innovations to improve your investment performance Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest. In the book, readers will learn how to: Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Download or read book AI Machine Learning Inference Explained A Beginner s Guide written by M.B. Chatfield and published by . This book was released on with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash the Power of AI with Machine Learning Inference In today's data-driven world, artificial intelligence (AI) is rapidly transforming industries and reshaping our lives. At the heart of this revolution lies machine learning, which empowers computers to learn from vast amounts of data and make intelligent decisions without explicit programming. AI/Machine Learning Inference Explained: A Beginner's Guide is your comprehensive guide to understanding and implementing inference, the crucial process of applying machine learning models to real-world problems. Through clear explanations you'll gain a solid foundation in the principles and practices of inference, enabling you to: Grasp the fundamental concepts of machine learning and AI Discover the different types of machine learning models Understand the role of inference in machine learning Learn various inference techniques, including classification, regression, and anomaly detection Apply inference to solve real-world problems in various domains Whether you're a tech enthusiast, a data analyst, or a budding AI professional, this book will equip you with the knowledge and skills you need to harness the power of machine learning inference and make a meaningful impact in the AI landscape. Embrace the future of AI: Start learning machine learning inference today! #AIinference #MachineLearning #AI #FutureofTechnology #DataScience #ArtificialIntelligence #MachineLearningBook #AIbook #AIforBeginners #PredictiveAnalytics #AIInnovation #BigData #DeepLearning #TechTrends #DataDriven #LearnAI #AIApplications

Download or read book Introduction to Machine Learning The Simplified Beginner s Guide written by LucieArt and published by Selfpublishing . This book was released on 2024-08-29 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Introduction to Machine Learning: The Simplified Beginner’s Guide" is your gateway to understanding the fundamentals of machine learning in just 20 pages. This concise guide is designed for beginners who want to grasp the essential concepts and applications of machine learning without getting bogged down by technical jargon. From the basics of algorithms and models to practical applications and future trends, this book covers it all in a clear and accessible manner. Whether you're looking to enhance your career or just curious about the impact of machine learning, this guide provides a solid foundation to get you started.

Download or read book Who is Fourier written by Transnational College of LEX. and published by . This book was released on 1995 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many people give up on math in high school - they do not feel comfortable with it, or they do not see the need for it in everyday life. These "mathematically-challenged" people may have had little recourse available in the past. Now, however, there is LRF's Who is Fourier?, which takes readers gently by the hand and helps them with both simple and intimidating concepts alike. By using everyday examples it enables the reader to develop an understanding of the language of Fourier's wave analysis. For instance, Fourier Series is explained with a comparison to the contents of 'Veggie-veggie' juice! The student authors take the reader along on their adventure of discovery, creating an interactive work that gradually moves from the very basics ("What is a right triangle?") to the more complicated mathematics of trigonometry, exponentiation, differentiation, and integration. This is done in a way that is not only easy to understand, but actually enjoyable.

Download or read book A Beginner s Guide to Learning Analytics written by Srinivasa K G and published by Springer Nature. This book was released on 2021-04-19 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book A Beginner’s Guide to Learning Analytics is designed to meet modern educational trends’ needs. It is addressed to readers who have no prior knowledge of learning analytics and functions as an introductory text to learning analytics for those who want to do more with evaluation/assessment in their organizations. The book is useful to all who need to evaluate their learning and teaching strategies. It aims to bring greater efficiency and deeper engagement to individual students, learning communities, and educators. Covered here are the key concepts linked to learning analytics for researchers and practitioners interested in learning analytics. This book helps those who want to apply analytics to learning and development programs and helps educational institutions to identify learners who require support and provide a more personalized learning experience. Like chapters show diverse uses of learning analytics to enhance student and faculty performance. It presents a coherent framework for the effective translation of learning analytics research for educational practice to its practical application in different educational domains. This book provides educators and researchers with the tools and frameworks to effectively make sense of and use data and analytics in their everyday practice. This book will be a valuable addition to researchers’ bookshelves.

Download or read book Machine Learning for Beginners written by Ryan Knight and published by Ryan Knight. This book was released on 2024-05-08 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enter a world of algorithms, data, and artificial intelligence, this all-inclusive guide strips away the complexity of machine learning and AI, transforming them from daunting subjects into accessible and comprehendible concepts. Whether you're a total novice or a professional looking to broaden your knowledge, this guide provides a structured approach that walks you through the basics, right through to the cutting-edge applications of AI and machine learning. Crafted with the reader in mind, every chapter provides detailed explanations, relatable examples, and step-by-step instructions to ensure a comprehensive yet enjoyable learning experience. Inside this book, you'll discover: An introduction to the exciting world of machine learning and AI, making it accessible to everyone regardless of technical background. Comprehensive discussions on the foundational concepts of machine learning, including algorithms, data science principles, and the different types of machine learning. Deep dives into the transformative applications of AI and machine learning in industries such as healthcare, retail, finance, transportation, education, and entertainment. Practical guides on mastering the essential tools and techniques for building intelligent solutions, complete with hands-on exercises and examples. An exploration of the ethical considerations around AI and machine learning, and the responsibilities we have as practitioners. Future trends in machine learning and AI, providing a glimpse into what lies on the horizon. Ignite your journey into the fascinating world of machine learning and AI today. Unleash the power of data and algorithms, create intelligent solutions, and shape a better future. Are you ready to master the future? The opportunity is just a click away. Pick up your copy now, and let's get started!

Download or read book Mastering Microsoft Azure for AI A Beginner s Guide written by M.B. Chatfield and published by . This book was released on with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mastering Microsoft Azure for AI: A Beginner's Guide is the definitive guide for anyone who wants to learn how to build and deploy artificial intelligence (AI) solutions on Microsoft Azure. This comprehensive book covers everything you need to know, from the basics of AI to the latest Azure AI services and technologies. Learn the fundamentals of AI Explore Azure AI services and technologies Build and deploy your own AI solutions Whether you're a beginner or an experienced developer, Mastering Microsoft Azure for AI: A Beginner's Guide is the perfect resource for learning how to build and deploy AI solutions on Microsoft Azure.

Download or read book Deep Learning written by Dulani Meedeniya and published by CRC Press. This book was released on 2023-10-16 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising. The design of the DL models based on artificial neural networks is influenced by the structure and operation of the brain. This book presents a comprehensive resource for those who seek a solid grasp of the techniques in DL. Key features: Provides knowledge on theory and design of state-of-the-art deep learning models for real-world applications Explains the concepts and terminology in problem-solving with deep learning Explores the theoretical basis for major algorithms and approaches in deep learning Discusses the enhancement techniques of deep learning models Identifies the performance evaluation techniques for deep learning models Accordingly, the book covers the entire process flow of deep learning by providing awareness of each of the widely used models. This book can be used as a beginners’ guide where the user can understand the associated concepts and techniques. This book will be a useful resource for undergraduate and postgraduate students, engineers, and researchers, who are starting to learn the subject of deep learning.

Download or read book Unlocking the Power of Data A Beginner s Guide to Data Analysis written by Balasubramanian Thiagarajan and published by Otolaryngology online. This book was released on 2023-06-13 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to the world of data analysis! In today's data-driven era, the ability to effectively analyze and derive insights from data has become a vital skill for individuals and organizations across various domains. This book aims to serve as your comprehensive guide to understanding and performing data analysis, from the fundamental concepts to the practical applications. Chapter 1 introduces you to the fascinating realm of data analysis. We delve into the importance of data analysis in decision-making processes and highlight its role in gaining valuable insights and making informed choices. Understanding the power of data analysis sets the foundation for your journey ahead. Chapter 2 focuses on data entry, a crucial step in the data analysis process. We explore different methods and techniques for entering data accurately, ensuring the reliability and integrity of your dataset. Effective data entry practices are essential for obtaining meaningful results. In Chapter 3, we explore the different types of data analysis. Whether it's exploratory, descriptive, diagnostic, predictive, or prescriptive analysis, you will gain an understanding of each type and when to employ them in various scenarios. This chapter equips you with the knowledge to choose the appropriate analysis technique for your specific needs. To lay the groundwork for your data analysis journey, Chapter 4 familiarizes you with the basic terminology commonly used in the field. From variables and observations to measures of central tendency and variability, this chapter ensures you have a solid grasp of the foundational concepts necessary for effective data analysis. Chapter 5 focuses on setting up your data analysis environment. We guide you through the process of installing the necessary software and configuring your data workspace. Creating an optimal environment is crucial for seamless and efficient data analysis. Data preprocessing takes center stage in Chapter 6. We delve into the essential steps of data cleaning, transformation, and handling missing values. By mastering these techniques, you will be able to prepare your data for analysis, ensuring its quality and usability. In Chapter 7, we explore the exciting world of data exploration and visualization. Understanding the distribution of data and identifying relationships between variables are key aspects of uncovering meaningful insights. We delve into creating various charts and graphs to visually represent data, aiding in its interpretation and analysis. Chapter 8 introduces you to statistical analysis techniques. Descriptive statistics help us summarize and describe data, while inferential statistics enable us to make inferences and draw conclusions about populations based on sample data. Additionally, hypothesis testing allows us to validate our assumptions and test specific predictions. Predictive analytics takes the spotlight in Chapter 9. We explore techniques such as linear and logistic regression, decision trees, and clustering algorithms. These techniques empower you to make predictions and forecasts based on historical data, providing valuable insights for decision-making. Chapter 10 is dedicated to machine learning, an exciting field within data analysis. We introduce the fundamentals of machine learning, including supervised and unsupervised learning algorithms. Understanding these concepts opens doors to more advanced data analysis techniques and applications. Ethics in data analysis takes center stage in Chapter 11. We delve into the critical considerations of privacy concerns, data bias, and fairness in data analysis. Ethical data practices are crucial to ensure the responsible and ethical use of data in analysis. Chapter 12 explores the wide-ranging applications of data analysis. We delve into the domains of business analytics, healthcare analytics, sports analytics, and social media analytics, highlighting how data analysis drives insights and informs decision-making in these fields. Finally, Chapter 13 serves as a conclusion and sets you on the path for further learning and development. We recap the key concepts covered in the book, provide tips for advancing your data analysis skills, and discuss future trends and innovations in the field. We hope this book serves as a valuable resource in your data analysis journey. Whether you are a student, professional, or data enthusiast, we believe that understanding and applying data analysis.

Download or read book DATA DRIVEN MARKETING IN THE AGE OF ARTIFICIAL INTELLIGENCE written by Dr. Raghava R. Gundala and published by Xoffencerpublication. This book was released on 2024-03-20 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to maximize the effectiveness of brand communication and propel the expansion of a company, data-driven marketing is a strategic strategy that makes use of consumer data. It entails gathering, analyzing, and making use of data from a variety of sources in order to obtain insights about the behavior, tastes, and trends of different types of customers. This information is then used to create marketing strategies, messaging, and campaigns to particular audiences, which ultimately results in marketing efforts that are more personalized and successful. The expansion of online platforms and the introduction of digital technology have both played a vital role in the development of data-driven marketing. Today's organizations have access to large volumes of data that are created by interactions with customers, activity on social media platforms, visits to websites, and other digital touchpoints. The abundance of data that is available to marketers gives them with important information on the demographics, interests, purchasing history, and online activity of their target audience population. The use of data has evolved into an essential component of successful marketing campaigns in this era of digital technology. The use of data-driven marketing completely transforms the method in which firms comprehend and interact with their clientele clients.[1] Businesses have the ability to get significant insights into the behavior, tastes, and trends of their customers by using the power of data analytics. This introduction serves as a doorway to explore the ideas, practices, and advantages of data-driven marketing. It gives organizations the ability to harness data to drive growth, improve customer connections, and maintain a competitive advantage in a market that is highly competitive. We invite you to accompany us on a trip into the realm of data-driven marketing, where each click, interaction, and transaction holds the key to unlocking new possibilities and driving success. Now that we have a better understanding of data-driven marketing, we will investigate the ways in which companies may efficiently gather, analyze, and make use of data in order to personalize their marketing efforts.

Download or read book AI Unlocked A Beginner s Guide to Understanding and Exploring Artificial Intelligence written by Dizzy Davidson and published by Pure Water Books. This book was released on 2024-07-24 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you find yourself puzzled by the complexities of artificial intelligence? Are you eager to understand how AI is transforming our world but don’t know where to start? Do you want to explore the fascinating world of AI without feeling overwhelmed? Yes, you can master the basics of AI and unlock its potential! “AI Unlocked: A Beginner’s Guide to Understanding and Exploring Artificial Intelligence” is your ultimate guide to demystifying AI. This comprehensive book covers everything from the history and types of AI to its applications in various fields like healthcare, education, transportation, and more. Designed for beginners, this book makes AI accessible and engaging. Benefits of Reading This Book: Build a Strong Foundation: Gain a clear understanding of AI concepts and terminology. Explore Real-World Applications: Learn how AI is used in everyday life and various industries. Stay Ahead of the Curve: Keep up with the latest trends and advancements in AI. Practical Insights: Discover how to apply AI concepts in real-world scenarios. Why This Book is a Good Answer for Those Seeking to Learn More About AI: Beginner-Friendly: Written in an easy-to-understand language, perfect for those new to AI. Comprehensive Coverage: Covers a wide range of topics, from AI history to its future. Engaging Content: Includes real-life examples, case studies, and interactive elements to keep you engaged. Expert Insights: Provides insights from AI experts and thought leaders. More Bullet Points: Demystify the complexities of AI. Learn AI concepts and terminology. Explore AI applications in healthcare, education, and more. Stay updated with the latest AI trends. Gain practical insights for real-world applications. Call to Action: Get your copy of “AI Unlocked: A Beginner’s Guide to Understanding and Exploring Artificial Intelligence” today and embark on a journey to become knowledgeable about AI. Let this book guide you through the fascinating world of AI and help you stay ahead in the tech-savvy world.

Download or read book Data Driven Systems and Intelligent Applications written by Mangesh M. Ghonge and published by CRC Press. This book was released on 2024-10-09 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively discusses basic data-driven intelligent systems, the methods for processing the data, and cloud computing with artificial intelligence. It presents fundamental and advanced techniques used for handling large user data, and for the data stored in the cloud. It further covers data-driven decision-making for smart logistics and manufacturing systems, network security, and privacy issues in cloud computing. This book: Discusses intelligent systems and cloud computing with the help of artificial intelligence and machine learning. Showcases the importance of machine learning and deep learning in data-driven and cloud-based applications to improve their capabilities and intelligence. Presents the latest developments in data-driven and cloud applications with respect to their design and architecture. Covers artificial intelligence methods along with their experimental result analysis through data processing tools. Presents the advent of machine learning, deep learning, and reinforcement technique for cloud computing to provide cost-effective and efficient services. The text will be useful for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer engineering, manufacturing engineering, and production engineering.