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This issue of Library Technology Reports argues that the near future of library work will be enormously impacted and perhaps forever changed as a result of artificial intelligence (AI) and machine learning systems becoming commonplace.
This proceedings volume provides a multifaceted perspective on current challenges and opportunities that organizations face in their efforts to develop and grow in an ever more complex environment. Featuring selected contributions from the 2019 Griffiths School of Management Annual Conference (GSMAC) on Business, Entrepreneurship and Ethics, this book focuses on the role of creativity, technology and ethics in facilitating the transformation organizations need in order to be ready for the future and succeed. Growth and development have always been imperative for people, organizations, and societies and a relevant topic in the management sciences. Globalization, along with dramatic changes in social, cultural, and technological progress, are the main factors that determine the current conditions for development, putting forth a new set of challenges and opportunities that are putting pressure on organisations to adapt. Although technology and creativity seem to be the mantra for success in this new context, issues around the ethics of these two factors also seem to be crucial to the sustainability of growth in organizations. Featuring contributions on topics such as academic marketing, technology in healthcare organizations, ethical issues in hospitality, artificial intelligence and data mining, this book provides research and tools for students, professors, practitioners and policy makers in the fields of business, management, public administration and sociology.
Information in today’s modernized world has become much more attainable with the use of technology. A resource that has fallen victim to this are library services. What was once a staple of knowledge and communication has failed to keep pace with recent advancements in information service providers. Library practitioners need to learn how to manage change, build influence, and adapt their services to remain relevant within local communities. Libraries can continue to play a key role in future aspects of information provision, but proper research is a necessity. Managing and Adapting Library Information Services for Future Users is a collection of innovative research that encapsulates practices, concepts, ideas, and proposals that would chart pathways for libraries of all types to envision and understand how to thrive and remain relevant in the competitive information provision environment. It is expected to motivate librarians and information scientists to probe further into how libraries would better serve user communities of the 21st century who have options of accessing information from sources other than from libraries. While highlighting topics including artificial intelligence, human design thinking, and alternative finance, this book is ideally designed for librarians, information specialists, architects, data scientists, researchers, community development practitioners, policymakers, faculty members, and students seeking current research on emerging advancements in library optimization.
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
Introduces the main algorithms and ideas that underpin machine learning techniques and applications Keeps mathematical prerequisites to a minimum, providing mathematical explanations in comment boxes and highlighting important equations Covers modern machine learning research and techniques Includes three new chapters on Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models Offers Python, R, and MATLAB code on accompanying website: http://www.dcs.gla.ac.uk/~srogers/firstcourseml/"
Comparing the human brain with so-called artificial intelligence, the author probes past, present, and future attempts to create machine intelligence
With the constant evolution of technology, libraries must grapple with the urgent need to adapt or face obsolescence. The integration of artificial intelligence (AI) into library operations presents many new opportunities as well as a complex array of challenges. The traditional roles of libraries, as pillars of knowledge and information, are being reshaped by AI, compelling institutions to reassess their relevance in an ever-evolving digital landscape. The urgency of this intersection between libraries and AI is emphasized by the necessity to revolutionize outdated systems, and it is in this dynamic context that Applications of Artificial Intelligence in Libraries emerges as an essential guide. The book addresses the ethical implications of AI-enabled libraries, offering strategies for navigating privacy concerns and potential challenges in the implementation of AI. It serves as a strategic guide for evaluating the impact and effectiveness of AI initiatives, developing policies and practices centered around AI, and training librarians for the inevitable integration of AI into their roles. By fostering collaboration between librarians, researchers, and AI experts, this book aims to empower professionals to navigate the transformative journey that AI is ushering in for libraries, fostering innovation, collaboration, and the creation of more effective and user-centric library services.
Create AI applications in Python and lay the foundations for your career in data science Key FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail with interesting examplesMaster core AI concepts with engaging activitiesBook Description Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! What you will learnUnderstand the importance, principles, and fields of AIImplement basic artificial intelligence concepts with PythonApply regression and classification concepts to real-world problemsPerform predictive analysis using decision trees and random forestsCarry out clustering using the k-means and mean shift algorithmsUnderstand the fundamentals of deep learning via practical examplesWho this book is for Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it’s recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI and ML and their origin and current state. The second and third parts delve into conceptual and theoretic aspects of static and dynamic ML techniques. The forth part describes the practical applications where presented techniques can be applied. The fifth part introduces the user to some of the implementation strategies for solving real life ML problems. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals. It makes minimal use of mathematics to make the topics more intuitive and accessible. Presents a full reference to artificial intelligence and machine learning techniques - in theory and application; Provides a guide to AI and ML with minimal use of mathematics to make the topics more intuitive and accessible; Connects all ML and AI techniques to applications and introduces implementations.