Libros de Otros lenguajes, página 34 de 223

Este libro pretende ser una ayuda y un estímulo para aquellos que han decidido aprender a programar en C. Para ello, recoge una batería de ejercicios que ayudan a comprender con claridad cómo funcion

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

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

This book constitutes the refereed proceedings of the 19th International Conference on Theory and Applications of Satisfiability Testing SAT 2016 held in Bordeaux France in July 2016 The 31 regular papers 5 tool papers presented together with 3 invited talks were carefully reviewed and selected from 70 submissions The papers address different aspects of SAT including complexity satisfiability solving satisfiability applications satisfiability modulop theory beyond SAT quantified Boolean formula and dependency QBF

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

Quantum Computing for Healthcare Data Revolutionizing the Future of Medicine presents an advanced overview of the fundamentals of quantum computing from the transition of traditional to quantum computing to the challenges and opportunities encountered as various industries enter into the paradigm shift The book investigates how quantum AI quantum data processing and quantum data analysis can best be integrated into healthcare data systems The book also introduces a range of case studies which feature applications of quantum computing in connected medical devices medical simulations robotics medical diagnosis and drug discovery The book will be a valuable resource for researchers graduate students and professional programmers and computer engineers working in the areas of healthcare data management and analytics blockchain IoT and big data analytics

This well balanced comprehensive and engaging review surveys the development of Artificial Intelligence over the last sixty years and highlights the likely transformative effects of AI on society ov

Master machine learning by writing code one line at a time from simple learning programs all the way to a true deep learning system Tackle the hard topics by breaking them down so they re easier to understand and build your confidence by getting your hands dirty

The metaverse a hybrid society of the real and the virtual is attracting significant attention from academia to industry and is starting to change the world

How to empower people and communities with user centric data ownership transparent and accountable algorithms and secure digital transaction systems Data is now central to the economy government and health systems so why are data and the AI systems that interpret the data in the hands of so few people Building the New Economy calls for us to reinvent the ways that data and artificial intelligence are used in civic and government systems Arguing that we need to think about data as a new type of capital the authors show that the use of data trusts and distributed ledgers can empower people and communities with user centric data ownership transparent and accountable algorithms machine learning fairness principles and methodologies and secure digital transaction systems It s well known that social media generate disinformation and that mobile phone tracking apps threaten privacy But these same technologies may also enable the creation of more agile systems in which power and decision making are distributed among stakeholders rather than concentrated in a few hands Offering both big ideas and detailed blueprints the authors describe such key building blocks as data cooperatives tokenized funding mechanisms and tradecoin architecture They also discuss techn

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

What is artificial intelligence What problems does it solve Should we fear its potential In this highly accessible guide to the subject Richard Urwin explains how AI came about and how it has developed over the years through the construction of ever more sophisticated computer programs From primitive calculators and early robotics to stock market analytics and ChatGPT readers can explore the history and far reaching capabilities of this dynamic field and its potentially frightening possibilities Includes The History of Artificial Intelligence Data mining and Statistics Deep learning Swarm Intelligence The singularity By turns fascinating and scary Artificial Intelligence will take the reader on an amazing journey of this field s world changing potential

An accessible explanation of the technologies that enable such popular voice interactive applications as Alexa Siri and Google Assistant Have you talked to a machine lately Asked Alexa to play a song asked Siri to call a friend asked Google Assistant to make a shopping list This volume in the MIT Press Essential Knowledge series offers a nontechnical and accessible explanation of the technologies that enable these popular devices Roberto Pieraccini drawing on more than thirty years of experience at companies including Bell Labs IBM and Google describes the developments in such fields as artificial intelligence machine learning speech recognition and natural language understanding that allow us to outsource tasks to our ubiquitous virtual assistants Pieraccini describes the software components that enable spoken communication between humans and computers and explains why it s so difficult to build machines that understand humans He explains speech recognition technology problems in extracting meaning from utterances in order to execute a request language and speech generation the dialog manager module and interactions with social assistants and robots Finally he considers the next big challenge in the development of virtual assistants building