Data og IT

Generative AI in Action presents concrete examples, insights, and techniques for using LLMs and other modern AI technologies successfully.

The increasing prominence of Generative AI presents healthcare integration opportunities. From generating valuable patient insights to automating operations, streamlining patient care, and implementing preventive technologies, Generative AI has the potential to usher in a new era of productivity and profitability for healthcare stakeholders.

This introductory text explores the key concepts of session types, which codify the structure of communication, making software more reliable and easier to construct. Complemented by examples and exercises throughout, it serves as an entry point to the topic for graduate students and researchers.

DESCRIPTIONGenerative AI for Financial Services is a book targeted at any AI practitioner who wants to understand how generative AI works on a fundamental level and extend that learning to risks, challenges, and opportunities in regulated industries like financial services.This book explores generative AI and its applications in financial services. It starts by explaining key concepts, differences from traditional AI, and the generative AI lifecycle. Readers learn about foundation models, transfer learning, and implementation strategies, including fine-tuning and training models. Practical use cases like improving customer experiences, automating ESG analysis, and optimizing contact centers are covered. The book also addresses challenges like model bias, ethics, and compliance while focusing on building trustworthy AI with fairness and accountability. Finally, it highlights MLOps and FMOps for efficient AI model deployment and management in production environments.By the end of this book, you will be well-equipped to navigate the exciting world of generative AI and confidently apply its transformative potential within the financial services landscape.KEY FEATURES¿ Evolve from a generative AI enthusiast to an advanced practitioner in generative AI.¿ Learn effective ways of building generative AI solutions for financial services.¿ Become familiar with the upcoming trends in generative AI space.WHAT YOU WILL LEARN¿ Learn about popular use-cases, challenges, risks in financial services, and how to overcome those.¿ Learn how to launch and scale generative AI applications in regulated environments like financial services, expanding from tens to thousands of use cases.¿ Understand the operational aspects of AI, including MLOps and FMOps.¿ Address challenges and ethical considerations in AI implementation.WHO THIS BOOK IS FORThis book is suitable for generative AI engineers, prompt engineers, ML engineers, data scientists, AI/ML, and technical leaders in financial services.

The proceedings of the Annual International Conference on Recent Trends in Healthcare Innovation (AICRTHI 2024) is a compilation of groundbreaking research and advancements in healthcare technology, artificial intelligence, and collaborative healthcare solutions. It serves as a guide for emerging trends in modern healthcare innovation.

This book serves as an insightful resource for understanding the transformative role of AI in optimizing design processes across a variety of fields. It explores foundational concepts, advanced methodologies, and real-world applications, offering a comprehensive guide to leveraging AI for innovative design solutions.

This book analyzes blockchain in the metaverse ecosystem and its future, starting with clear definitions of AI, blockchain, and Metaverse. It discusses the evolution of the blockchain and addresses government involvement, virtual real estate, and emerging security concerns.

The difference between growing your business and going out of business is your ability to think strategically. The problem: Leaders are stuck in the operational weeds, while their competition gains an edge with AI. The time to act is now.In The AI-Driven Leader, you'll learn how to: Escape operational overwhelm and lead with strategic clarityCollapse the time for turning data into decisions 10x the impact of every employeeApply real-world examples and prompts to get immediate resultsThe AI-Driven Leader gives you a simple path to harness AI as your Thought Partner. Grow your business, outpace the competition, and get more done in less time.

How and why the US government gave up its control of ICANN, the global coordinator of internet names, numbers, and protocols—and what the geopolitical consequences were.In 1997 the U.S. decided that the Internet should be governed not by governments, but by something called the “global Internet community.” In Declaring Independence in Cyberspace,Milton Mueller tells the story of why it took 20 years of organizational and geopolitical stuggle to make that happen.ICANN (Internet Corporation for Assigned Names and Numbers), created in 1998, was the US government’s answer to the question of who would control the Internet registries—a key part of the Internet infrastructure supporting domain names, network numbers, IP addresses, and other protocol parameters. Originally, ICANN was a bold institutional innovation based on a vision of Internet governance that was thoroughly globalized and independent of nation-states. Declaring Independence in Cyberspace explains where this vision came from, the problems posed by its implementation, and the organization’s near-self destruction in its first five years. The U.S. government refused to let go of ICANN for 15 years, triggering geopolitical conflicts over sovereignty and U.S. power. Mueller details why, what prompted its change of heart, and how the problem of making ICANN accountable to its community in the absence of U.S. government control sparked a political battle in Washington. His account gets to the very heart of a pressing question with profound global implications: Is state sovereignty the immutable foundation of global governance, or do new technological capabilities change the model?

Someone has stolen Sally Jones's name. But why? What does she want? As Sally investigates, she uncovers a dark web of lies, crime and danger in this compulsive, twisty thriller.

DESCRIPTIONTableau is one of the leading business intelligence and data visualization tools that fulfill almost all the requirements for getting insights from huge data and solving complex business queries using simple and complex visualizations. This book covers all the features supported by Tableau, from basics to advanced.Master data storytelling with Tableau by learning to connect, clean, and analyze data from various sources. This book covers essential chart types like bar, line, and pie charts while introducing advanced features like filters, LOD expressions, and dual-axis charts. Create interactive dashboards by combining visualizations, adding controls, and customizing designs to engage your audience. Use storytelling techniques to present insights effectively. With advanced visualizations like combo and Gantt charts, this guide equips you with the skills to communicate data clearly and make informed, data-driven decisions.This book begins with very basic information that even a beginner can understand. Gradually, the book covers intermediate and advanced features of Tableau, so it can help readers of all levels become experts in Tableau.WHAT YOU WILL LEARN¿ Understand different types of data sources and how to connect them.¿ Learn techniques for cleaning and preparing data for visualization.¿ Perform calculations, aggregations, and level of detail (LOD) expressions.¿ Create both, simple and advanced visualizations to present data.¿ Design visually engaging dashboards and storyboards to answer business questions effectively.WHO THIS BOOK IS FORThis book is for students and professionals who want to learn and have a rewarding career in data visualization using Tableau. It is also for anyone who wants to become a data analyst, Tableau developer, business analyst, etc.

DESCRIPTIONFor most modern-day data, graph data models are proving to be advantageous since they facilitate a diverse range of data analyses. This has spiked the interest and usage of graph databases, especially Neo4j. We study Neo4j and cypher along with various plugins that augment database capabilities in terms of data types or facilitate applications in data science and machine learning using plugins like graph data science (GDS).A significant portion of the book is focused on discussing the structure and usage of graph algorithms. Readers will gain insights into well-known algorithms like shortest path, PageRank, or Label Propagation among others, and how one can apply these algorithms in real-world scenarios within a Neo4j graph.Once readers become acquainted with the various algorithms applicable to graph analysis, we transition to data science problems. Here, we explore how a graph's structure and algorithms can enhance predictive modeling, prediction of connections in the graph, etc. In conclusion, we demonstrate that beyond its prowess in data analysis, Neo4j can be tweaked in a production setup to handle large data sets and queries at scale, allowing more complex and sophisticated analyses to come to life.KEY FEATURES¿ Utilizing graphs to improve search and recommendations on graph data models.¿ Understand GDS and Neo4j graph algorithms including cluster detection, link prediction, and centrality.¿ Complex problem-solving for predicting connections, application in ML pipelines and GNNs using graphs.WHAT YOU WILL LEARN¿ Understand Neo4j graphs and how to effectively query them with cypher.¿ Learn to employ graphs for effective search and recommendations around graph data.¿ Work with graph algorithms to solve problems like finding paths, centrality metrics, and detection of communities and clusters.¿ Explore Neo4j's GDS library through practical examples.¿ Integrate machine learning with Neo4j graphs, covering data prep, feature extraction, and model training.WHO THIS BOOK IS FORThe book is intended to serve as a reference for data scientists, business analysts, graph enthusiasts, and database developers and administrators who work or intend to work on extracting critical insights from graph-based data stores.

If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.By working with a single case study throughout this thoroughly revised book, youll learn the entire process of exploratory data analysisfrom collecting data and generating statistics to identifying patterns and testing hypotheses. Youll explore distributions, rules of probability, visualization, and many other tools and concepts.New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries.Develop an understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyImport data from most sources with Python, rather than rely on data thats cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

The text discusses topics such as safety in close human-robot interaction, machine vision applications for robotics in healthcare, robotic interactions, and control for wearable devices. It further covers explainable artificial intelligence in medical imaging, the interpretability of healthcare models, and explainable healthcare frameworks.

This self-contained monograph reports the recent approaches, methods and practices of technology-enabled personalized learning. It serves to provide some useful references for researchers and practitioners in the field in conceptualizing and deploying personalized learning.

This text discusses the techniques to convert agricultural knowledge in the context of ontology and assist grape growers by providing this knowledge through decision support system. It presents the design & development of an ontology-based decision support system for integrated crop management.

The text focuses on the theory, design, and implementation of the Internet of Things in a modern communication system. It will be useful to senior undergraduate, graduate students, and researchers in diverse fields domains including electrical engineering, electronics and communications engineering.

This book examines the latest developments in AI-based metaheuristics algorithms with applications in information security for digital media. It highlights the importance of several security parameters, their analysis, and validations for different practical applications.