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This book comprehensively covers the topic of recommender systems which provide personalized recommendations of products or services to users based on their previous searches or purchases Recommender system methods have been adapted to diverse applications including query log mining social networking news recommendations and computational advertising This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity The chapters of this book are organized into three categories Algorithms and evaluation These chapters discuss the fundamental algorithms in recommender systems including collaborative filtering methods content based methods knowledge based methods ensemble based methods and evaluation Recommendations in specific domains and contexts the context of a recommendation can be viewed as important side information that affects the recommendation goals Different types of context such as temporal data spatial data social data tagging data and trustworthiness are explored Advanced topics and applications Various robustness aspects of recommender systems such as shilling systems attack models and their defenses are discussed In addition recent topics such as learning to rank multi armed bandits gr

Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear.

Enterprises as well as individuals are racing to reap the benefits of AI However in most cases they are doing so without understanding the technology or its implications and risks which can be significant Artificial Intelligence A Guide for Everyone is a step in addressing that gap by providing information that readers can easily understand at every level This book aims to provide useful information to those planning developing or using AI which has the potential to transform industries and shape the future Whether you are stepping into the world of AI for the first time or are a seasoned professional seeking deeper insights this comprehensive guide ensures that both beginners and experienced individuals find value within its pages Artificial Intelligence A Guide for Everyone encompasses theoretical as well as practical aspects of AI across various industries and applications It demystifies AI by explaining in a language that non techies can follow its history different types differentiating technologies and various aspects of implementation It explains the connection between AI theory and real world application across diverse industries and how it fuels innovation Whether you are an executive student professional seasoned businessperson or

Discover how to achieve business goals by relying on high quality robust data In Data Quality Empowering Businesses with Analytics and AI veteran data and analytics professional delivers a practical and hands on discussion on how to accelerate business results using high quality data In the book you ll learn techniques to define and assess data quality discover how to ensure that your firm s data collection practices avoid common pitfalls and deficiencies improve the level of data quality in the business and guarantee that the resulting data is useful for powering high level analytics and AI applications The author shows you how to Profile for data quality including the appropriate techniques criteria and KPIs Identify the root causes of data quality issues in the business apart from discussing the 16 common root causes that degrade data quality in the organization Formulate the reference architecture for data quality including practical design patterns for remediating data quality Implement the 10 best data quality practices and the required capabilities for improving operations compliance and decision making capabilities in the business An essential resource for data scientists data analysts business intelligence professionals chief technology and

Computational Intelligence and Blockchain in Complex Systems System Security and Interdisciplinary Applications provides readers with a guide to understanding the dynamics of AI machine learning and computational intelligence in blockchain and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications This book examines the role of computational intelligence and machine learning in the development of algorithms to deploy blockchain technology across a number of applications including healthcare insurance smart grid smart contracts digital currency precision agriculture and supply chain The authors cover the unique and developing intersection between cyber security and blockchain in modern networks as well as in depth studies on cybersecurity challenges and multidisciplinary methods in modern blockchain networks Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods especially the complex algorithms involved in blockchain security aspects for hashing coding and decoding This book also provides readers with the most in depth technical guide to the intersection of computational intelligence and blockchain two of the most

Blockchain Technology Solutions for the Security of IoT Based Healthcare Systems explores the various benefits and challenges associated with the integration of blockchain with IoT healthcare systems focusing on designing cognitive embedded data technologies to aid better decision making processing and analysis of large amounts of data collected through IoT This book series targets the adaptation of decision making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and Internet of Things IoT problems can be handled in practice Current Internet of Things IoT based healthcare systems are incapable of sharing data between platforms in an efficient manner and holding them securely at the logical and physical level To this end blockchain technology guarantees a fully autonomous and secure ecosystem by exploiting the combined advantages of smart contracts and global consensus However incorporating blockchain technology in IoT healthcare systems is not easy Centralized networks in their current capacity will be incapable to meet the data storage demands of the incoming surge of IoT based healthcare wearables

La Serie Enter de Computación ha sido creada para enseñar a los usuarios el camino fácil en el uso de algunas de las aplicaciones más conocidas para computadores personales. Access 2.0 desarrolla de manera concisa y practica la utilizacion de las herramientas de uno de los programas para el manejo de bases de datos relacionales mas potentes y populares bajo el ambiente Windows. Incluye disquete con ejemplos.

El objetivo de este libro es enseñarle a manejar un gestor de bases de datos. A lo largo de sus páginas aprenderá a crear y manejar tablas, formularios, consultas e informes. El libro está dirigido tanto a estudiantes como a profesionales interesados en conseguir rapidamente conocimientos practicos sobre bases de datos. El programa sobre el que hemos basado tanto las explicaciones teoricas como los ejercicios practicos es el Microsoft Access.INDICE: Capitulo 1. Introduccion a las Bases de Datos 11. Capitulo 2. Introduccion a Access 33. Capitulo 3. Creacion de Tablas 49. Capitulo 4. Actualizacion de Tablas 67. Capitulo 5. Creacion de Tablas con el Asistente 87. Capitulo 6. Formularios 109. Capitulo 7. Algunas Operaciones Adicionales 127. Capitulo 8. Objetos OLE 147. Capitulo 9. Construccion de Expresiones 165. Capitulo 10. Tablas relacionadas entre si 175. Capitulo 11. Consultas de Tablas Simples 195. Capitulo 12. Consultas de Tablas Relacionadas 211. Capitulo 13. Informes (I) 235. Capitulo 14. Informes (II) 259. Capitulo 15. Impresion en Access 275. Anexo A. Ejercicios Teoricos 287. Anexo B. Ejercicios Practicos 303. Indice Alfabetico 321.

Los libros de la Serie Enter son una colección de guías informáticas que pretenden orientar al usuario en el aprendizaje rápido y fácil de las aplicaciones más populares. Este título incluye el programa Access 7.0 para Windows 95 que es un administrador de bases de datos sencillo de utilizar para el mantenimiento eficiente de informacion. Se desarrollan conceptos generales como la creacion de bases de datos tablas formularios consultas e informes. Cada tema esta acompañado de un ejemplo que ilustra el conocimiento que se quiere dar a entender. Incluye disquete con archivos de practicas.