Libros de Programación, página 92 de 316

This book provides a comprehensive analysis of the tools and techniques used today for designing and modeling of efficient and robust swarm intelligence based systems highly or fully decentralized semi autonomous highly scalable infrastructures in various real life scenarios Among others the book reviews the use of the swarm intelligence paradigm in financial investment blockchain protocols design shared transportation systems communication networks bioinformatics and military applications Theoretical and practical limitations of such systems as well as trade offs between the various economic and operational parameters of the systems are discussed The book is intended for researchers and engineers in the fields of swarm systems economics agriculture nutrition and operation research

Can computers think? Can they use reason to develop their own concepts, solve complex problems, understand our languages? This updated edition of a comprehensive survey explores these and other fascinating questions. Ideal for both lay readers and students of computer science, its well-illustrated, easy-to-read discussions include problem-solving methods and representations, game playing, heuristic search theory, neural networks, robot systems, and many other subjects.

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.

User experience UX design practices have seen a fundamental shift as more and more software products incorporate machine learning ML components and artificial intelligence AI algorithms at their core This book will probe into UX design s role in making technologies inclusive and enabling user collaboration with AI AI ML based systems have changed the way of traditional UX design Instead of programming a method to do a specific action creators of these systems provide data and nurture them to curate outcomes based on inputs These systems are dynamic and while AI systems change over time their user experience in many cases does not adapt to this dynamic nature Applied UX Design for Artificial Intelligence will explore this problem addressing the challenges and opportunities in UX design for AI ML systems look at best practices for designers managers and product creators and showcase how individuals from a non technical background can collaborate effectively with AI and Machine learning teams You Will Learn Best practices in UX design when building human centric AI products or features Ability to spot opportunities for applying AI in their organizations Advantages and limitations of AI when building software products Ability to collaborate and commun

With detailed notes tables and examples this handy reference will help you navigate the basics of structured machine learning Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project

If you re looking to make a career move from programmer to AI specialist this is the ideal place to start Based on Laurence Moroney s extremely successful AI courses this introductory book provides a hands on code first approach to help you build confidence while you learn key topics

Author Ryan Sleeper one of the world s most qualified Tableau consultants complements his web posts and instructional videos with this guide to give you a firm understanding of how to use Tableau t

This book highlights the numerous potentials and concerns involved with using the metaverse The application areas of the metaverse is quite vast but it also includes security and privacy issues Hence along with the applications this book helps the reader understand these hidden security and privacy issues

¡Por fin una panorámica completa y concisa de Oracle8 para los nuevos usuarios! Este libro le presentará los conceptos esenciales de la última versión de este complejo y potente sistema de gestión de bases de datos y le enseñara los fundamentos de la instalacion consulta y gestion de su base de datos. Esta guia oficial autorizada por Oracle Corporation esta escrita por dos renombrados miembros de la comunidad Oracle expertos en bases de datos Michael Abbey y Michael J. Corey.

MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way This insightful guide takes you through what MLOps is and how it differs from DevOps and shows you how to put it into practice to operationalize your machine learning models

The expert guide to creating production machine learning solutions with ML NET ML NET brings the power of machine learning to all NET developers and Programming ML NET helps you apply it in real production solutions Modeled on Dino Esposito s best selling Programming ASP NET this book takes the same scenario based approach Microsoft s team used to build ML NET itself After a foundational overview of ML NET s libraries the authors illuminate mini frameworks ML Tasks for regression classification ranking anomaly detection and more For each ML Task they offer insights for overcoming common real world challenges Finally going far beyond shallow learning the authors thoroughly introduce ML NET neural networking They present a complete example application demonstrating advanced Microsoft Azure cognitive services and a handmade custom Keras network showing how to leverage popular Python tools within NET 14 time Microsoft MVP Dino Esposito and son Francesco Esposito show how to Build smarter machine learning solutions that are closer to your user s needs See how ML NET instantiates the classic ML pipeline and simplifies common scenarios such as sentiment analysis fraud detection and price prediction Implement data processing and training and produ