Este libro podría haber sido escrito por una inteligencia artificial, y no solamente por un humano en un documento de Word. Aunque, en parte, así fue. Con inteligencia artificial podemos escribir ensayos, incluso libros, y tambien, entre muchas posibilidades, predecir cuantos pacientes llegaran a un hospital con gripe dentro de quince dias, o detectar automaticamente una operacion fraudulenta con una tarjeta de credito. ¿Cuales son los limites de esta tecnologia? ¿Cuales son sus riesgos? ¿Cual es la mejor manera de aprovecharla? ¿Como desarrollar inteligencia artificial responsablemente? En ¿Como piensan las maquinas?, Fredi Vivas te invita a sumarte a un viaje fascinante, una aventura literaria que transita entre la realidad y la ficcion para demostrarnos que, independientemente del area o disciplina, la inteligencia artificial esta revolucionando la vida humana mucho mas de lo que creemos o soñamos. Y como no podia ser de otra forma, este es un libro interactivo, que incorpora tecnologia en sus paginas, y que propone al lector una experiencia multiplataforma. Apto para cualquiera que tenga como objetivo entender el mundo que se viene y estar a la vanguardia de la revolucion tecnologica, ¿Como piensan las maquinas? no requiere conocimientos tecnicos previos y apuesta por la curiosidad y el interes por el futuro.

Una visión inspiradora de nuestra convivencia con la IA. Un libro necesario para comprender el futuro inmediato, sus retos y oportunidades.¿Crees que estamos ante el apocalipsis de las máquinas? ¿Eres de los que ceden sus datos con total alegria? ¿Temes por tu trabajo y por tu seguridad en este futuro inmediato o piensas que este es el inicio de una nueva manera de trabajar para todos? ¿Crees que la inteligencia artificial puede superar a la natural o quiza piensas que son complementarias?Vidas futuras ofrece una vision realista sobre la inteligencia artificial y su impacto social. Por supuesto que la IA supondra un reto etico y economico, pero tambien tiene un potencial inmenso para mejorar temas fundamentales como el trabajo, la salud o la educacion.Cristina Aranda, linguista de formacion, se ha convertido contra todo pronostico en una de las mentes mas brillantes de nuestro pais en el ambito de la tecnologia, y explica en este libro con claridad y sentido del humor como podemos controlar y dirigir la IA para que sirva a los intereses de las personas.

La irrupción de la inteligencia artificial y sus desafíos para la especie humana.Un fantasma recorre nuestro presente: la inteligencia artificial. Desde finales de 2022, las herramientas digitales que permiten simular, expandir o complementar la inteligencia humana muestran una vertiginosa evolucion cuyos beneficios y potenciales riesgos para nuestra especie parecen hoy en dia imprevisibles. Aunque el concepto es aun algo difuso, cabe definir la inteligencia artificial como la capacidad que el ser humano ha otorgado a determinadas maquinas de aprender, razonar y comprender conceptos. Una mente infinita nos brinda un recorrido comprensible y riguroso por la historia, los procedimientos, la arquitectura tecnologica y los desafios de toda indole, tambien eticos y sociales, que se ocultan tras este salto de gigante de la humanidad hacia un futuro lleno de incognitas.

Build Real-World AI with Transformers Powered by PyTorch 2.0. Key Features Complete hands-on projects spanning NLP, vision, and speech AI. Interactive Jupyter Notebooks with real-world industry scenarios. Build a professional AI portfolio ready for career advancement. Book Description Transformer models have revolutionized AI across natural language processing, computer vision, and speech recognition. "Ultimate Transformer Models Using PyTorch 2.0" bridges theory and practice, guiding you from fundamentals to advanced implementations with hands-on projects that build a professional AI portfolio. This comprehensive journey spans 11 chapters, beginning with transformer foundations and PyTorch 2.0 setup. With this book, you will master self-attention mechanisms, tackle NLP tasks such as text classification and translation, and then expand into computer vision and speech processing. Advanced topics include BERT and GPT models, the Hugging Face ecosystem, training strategies, and deployment techniques. Each chapter features practical exercises that reinforce learning through real-world applications. By the end of this book, you will be able to confidently design, implement, and optimize transformer models for diverse challenges. So, whether revolutionizing language understanding, advancing computer vision, or innovating speech recognition, you will possess both theoretical knowledge and practical expertise to deploy solutions effectively across industries like healthcare, finance, and social media, positioning yourself at the AI revolutions forefront. What you will learn Build custom transformer architectures from scratch, using PyTorch 2.0. Fine-tune BERT, GPT, and T5 models for specific applications. Deploy production-ready AI models across NLP, vision, and speech domains. Master Hugging Face ecosystem for rapid model development and deployment. Optimize transformer performance, using advanced training techniques and hyperparameters. Create a professional portfolio showcasing real-world transformer implementations.

Power your AI Journey and Build the Future with Snowflake Cortex. Key Features Build enterprise-ready GenAI apps using Snowflake Cortex tools and APIs. Implement RAG, AI Agents, and Document AI with real-world precision. Explore practical Cortex use cases across industries and domains. Book Description Snowflake Cortex is redefining how modern enterprises build, scale, and deploy Generative AInatively within the data cloud. Ultimate Snowflake Cortex AI for Generative AI Applications is a hands-on, end-to-end guide designed for data professionals, engineers, and technical leaders eager to unlock the full power of Snowflakes native AI engine. The book begins by grounding you in the fundamentals of AI/ML within the Snowflake ecosystem before diving deep into the architecture, capabilities, and use cases of Snowflake Cortex. As you progress, youll explore Cortexs built-in machine learning functions, dive into prompt engineering, Retrieval-Augmented Generation (RAG), and learn how to leverage LLM functions effectively. Youll gain hands-on experience in fine-tuning models, translating natural language queries into actionable insights, and automating document processing using Cortexs Document AI. Practical chapters on security, governance, and cost discipline ensure youre prepared for enterprise-scale AI deployment. With real-world case studies and cross-industry applications, this book equips you with both the strategic understanding and technical skills to implement Generative AI at scale. Cortex is the future of enterprise AIdont just adapt to it, lead it. What you will learn Build and deploy Generative AI apps using Snowflake Cortex. Understand and apply Cortexs built-in LLM functions effectively. Fine-tune LLMs for domain-specific, enterprise-grade applications. Use RAG and prompt engineering for accurate AI responses. Extract insights from structured and unstructured enterprise data. Automate document workflows using Cortexs Document AI features. Solve cross-industry problems with real-world Cortex implementations.

Build, Scale and Optimize Cutting-Edge NLP with Llama for Next Gen AI. Key Features Explore Llamas evolution and innovations for next-gen NLP. Implement real-world NLP tasks with step-by-step examples. Fine-tune, optimize, and deploy Llama at enterprise scale. Book Description Llama models have rapidly emerged as a cornerstone in natural language processing, redefining how AI systems understand and generate human language. From their efficient architecture to the cutting-edge advancements in Llama 4, these models enable enterprises, researchers, and developers to build powerful, scalable, and responsible NLP solutions. This book, Ultimate Llama for Natural Language Processing (NLP), takes you on a structured journey through the evolution and applications of Llama. It begins with the foundations of the Llama series and its architecture, before progressing to core NLP tasks such as classification, summarization, sentiment analysis, and conversational AI. Subsequent chapters cover fine-tuning, transfer learning, optimization, and deployment at enterprise scale, with practical insights into real-world industry use cases. The book also addresses troubleshooting, ethical AI, and the future of multimodal and sparse Mixture-of-Experts models. Thus, by the end, readers will be well-equipped to train, adapt, and deploy Llama models across domains such as healthcare, finance, and customer engagement. What you will learn Understand Llamas evolution, architecture, and unique innovations in NLP. Implement core NLP tasks like classification, NER, and summarization. Fine-tune Llama for custom domains using advanced transfer learning. Optimize inference speed, and deploy Llama models at enterprise scale. Troubleshoot, monitor, and continuously improve Llama model performance. Apply Llama 4 to real-world industry use cases and multimodal AI.

Build Future-ready Enterprise AI with IBM Granite and Watsonx AI. Key Features Step-by-step instructions to install and configure Granite 3.0 using GitHub and VSCode on both Windows and Red Hat Linux systems. Build advanced prompt strategies using Python and Ansible to enhance LLM response accuracy and adaptability in enterprise scenarios. Prepare for the future of enterprise AI with forward-looking analysis of IBMs Granite platform evolution. Book Description IBM Granite 3.0 delivers enterprise-ready, open-source LLMs powered by Watsonx AImaking it essential for developers, data scientists, and IT professionals driving AI transformation. Ultimate IBM Granite for Enterprise Applications offers a structured, hands-on journey from foundational knowledge to real-world enterprise deployment. You will start by learning the principles of LLMs, and then unpack the architecture of IBM Granite 3.0. guided tutorials to walk you through the installation process using GitHub and VSCode, empowering you to replicate the setup on your systems. As you navigate through the book, you will delve deeper into advanced prompt engineering techniques to improve accuracy and performance, fine-tune Granite models for specialized business domains, and streamline DevOps automation using Red Hat Ansible Lightspeed. Throughout the book, code examples and Ansible playbooks ensure concepts that are not just explained, but applied. In the final chapters, you will focus on scaling, deploying, and maintaining Granite LLMs in production environmentscomplete with strategies for performance optimization, version upgrades, and enterprise integration. The book concludes with a forward-looking view into IBMs AI roadmap, helping you to align your strategy with what is next. Hence, whether you are building intelligent apps, modernizing DevOps, or planning long-term AI strategies, this book equips you to harness Granite 3.0s full power. What you will learn Set up IBM Granite 3.0, using GitHub and VSCode environments. Understand how IBMs LLM architecture powers enterprise-scale solutions. Automate system configuration, using Red Hat Ansible Lightspeed. Fine-tune Granite models to suit your domain-specific needs. Optimize AI deployments for enterprise performance and reliability. Anticipate Future AI Trends with IBMs Granite Roadmap.

Harness Genetic Algorithms to Build the Next Generation of Adaptive AI. Key Features Step-by-step tutorials on Genetic Algorithms, using PyGAD and DEAP. Real-world Genetic Algorithm applications in ML, DL, NLP, CV, and RL. Advanced coverage of evolutionary and metaheuristic algorithms. Integration of Genetic Algorithms with generative and agent-based AI systems. Book Description Genetic Algorithms (GAs) are nature-inspired optimization tools that help AI systems adapt, improve, and solve complex problems efficiently. Ultimate Genetic Algorithms with Python explains elaborately the fundamentals of GAs to practical, Python-based implementation, using PyGAD and DEAP. The book starts with a solid foundation, explaining how evolutionary principles can be applied to optimization tasks, search problems, and model improvement. You will also explore GA applications across multiple AI domains: optimizing machine learning workflows, evolving neural network architectures in deep learning, enhancing feature selection in NLP, improving performance in computer vision, and guiding exploration strategies in reinforcement learning. Each application chapter includes step-by-step coding examples, performance comparisons, and tuning techniques. The later sections focus on advanced metaheuristics, swarm intelligence, and integrating GAs with generative and agent-based AI systems. You will also learn how to design self-evolving, multi-agent frameworks, leverage swarm-based methods, and connect GAs to next-gen AI architectures such as Model Context Protocols (MCP). What you will learn Master the fundamentals and components of Genetic Algorithms. Implement GAs in Python, using PyGAD, DEAP, and PyTorch. Apply GAs for optimization, feature selection, and neural architecture search. Enhance AI workflows in ML, DL, NLP, CV, and RL with GAs. Explore metaheuristic and swarm-based algorithms for complex problem-solving. Integrate GAs into generative, multi-agent, and self-evolving AI systems.

Turn Financial Data into Decisions with the Power of FinGPT. Key Features Hands-on setup of FINGPT in real-world finance projects. End-to-end guide for automating financial reporting tasks. Case studies on market trends and sentiment prediction. Techniques to scale, fine-tune, and optimize FINGPT models. Book Description FINGPT is redefining how financial institutions analyze data, forecast trends, and make strategic decisions. As the financial sector embraces generative AI, understanding and applying FINGPT becomes essential for professionals seeking to stay competitive and innovative. Ultimate FINGPT for Financial Analysis takes you on a complete journeyfrom setting up your development environment and preparing financial datasets to building, fine-tuning, and deploying FINGPT models. The book covers all the vital concepts such as data cleaning, model training, prompt engineering, and real-world deployment. You will learn to automate financial reporting, generate accurate forecasts, perform sentiment analysis on news and reports, and simulate risk scenarios. Dedicated chapters on case studies and performance optimization provide deep insights into practical applications, while ethical considerations and scaling strategies ensure readiness for enterprise use. Hence, whether you are a finance expert aiming to integrate AI or a data scientist expanding into fintech, this book provides the tools, frameworks, and confidence to apply FINGPT in your work. So, do not get left behindstart transforming your financial analysis with AI today. What you will learn Apply FINGPT for financial forecasting and workflow automation. Build sentiment-aware models for trend and event prediction. Combine structured and unstructured data for deep insights. Generate reports and analytics, using AI-powered pipelines. Simulate risk scenarios, and plan proactive mitigations. Monitor FINGPT performance, using finance-specific KPIs.

Your Complete Roadmap to AWS AI Practitioner SuccessSimplified, Practical, and Designed to Help You Pass with Confidence. Key Features Gain in-depth knowledge of AWS AI services, Generative AI, and ethical considerations for business and technical use cases. Master essential AWS AI/ML tools to stay ahead in the evolving landscape of cloud-based artificial intelligence solutions. Prepare confidently with real-world examples, clear explanations, and targeted exam questions for the AWS AI Practitioner certification. Book Description In todays AI-powered world, earning the AWS Certified AI Practitioner (AIF-C01) certification is a powerful way to validate your skills, boost your credibility, and stand out in the competitive cloud job market. Ultimate AWS Certified AI Practitioner (AIF-C01) Exam Guide is a comprehensive, beginner-friendly roadmap for professionals, students, and decision-makers looking to master AI and Machine Learning on AWSand crack the AIF-C01 exam with confidence. Covering everything from AI and ML fundamentals to core AWS services like SageMaker, Bedrock, and Rekognition, this guide also explores Generative AI, vision and language-based AI use cases, and practical tools for personalization, security, and governance. Youll gain clarity on responsible AI principles, learn to identify and mitigate bias, and confidently navigate AWS best practices in ethics and compliance. Each chapter offers real-world examples, exam strategies, and practice questions designed to reinforce key concepts and simulate the exam environment. Whether youre technical or non-technical, the content is simplified for easy understandingwithout sacrificing depth or relevance. If youre serious about working in AI or cloud, this certification isnt just a bonusits becoming a must-have. Dont miss your chance to stay ahead of the curvemaster AWS AI and future-proof your career now. What you will learn Understand foundational concepts of AI, Machine Learning, and Generative AI for modern cloud applications. Gain hands-on experience with AWS AI/ML services like SageMaker, Bedrock and Rekognition to build intelligent solutions. Learn to build, train, fine-tune, and deploy machine learning models using Amazon SageMaker. Apply responsible AI practices by identifying and mitigating ethical risks, biases, and fairness issues in AI solutions. Secure your AI workloads through AWS best practices in governance, compliance, and data protection. Access targeted exam tips, mock questions, and real-world examples to confidently clear the AWS AI Practitioner certification.

Code smarter, Test faster, and Build better with GitHub Copilot! Key Features Master prompt engineering and multi-modal Copilot interactions. Use GitHub Copilot for real coding, testing, and DevOps tasks. Speed up development with AI-powered code and test generation. Book Description AI-assisted coding is transforming how software is builtfaster, smarter, and with fewer errors. GitHub Copilot leads this revolution by turning natural language into functional code, enabling developers to focus on solving problems rather than writing boilerplate. The Ultimate AI-Assisted Development with GitHub Copilot takes you step-by-step through mastering Copilot, starting with initial setup and basic use across multiple languages like Java, Python, TypeScript, Go, and C++. Youll explore prompt engineering techniques to craft effective instructions, leverage multi-modal inputs to interact beyond text, and unlock advanced features like Vibe Coding and Agent Mode to create context-aware, intelligent workflows. The book also covers integrating Copilot into testing and debugging processes, automating repetitive tasks, and embedding AI-powered coding into CI/CD pipelines to streamline DevOps practices. Whether youre building APIs, automating tests, refactoring code, or optimizing release workflows, this book teaches you how to collaborate with AInot just use it. Dont get left behindunlock the full potential of GitHub Copilot and future-proof your skills today. What you will learn Use GitHub Copilot effectively in Python, Java, Go, and C++. Write smart prompts to guide Copilot across coding scenarios. Build and debug applications using AI-generated code snippets. Enhance test automation and integrate Copilot into CI/CD flows. Leverage Agent Mode and Vibe Coding for intelligent automation. Adapt Copilot for education, framework design, and DevOps tasks.

Empowering Enterprises with Scalable, Intelligent AI Agents. Key Features Hands-on practical guidance with step-by-step tutorials and real-world examples. Build and deploy enterprise-grade LLM agents using the AutoGen framework. Optimize, scale, secure, and maintain AI agents in real-world business settings. Book Description In an era where artificial intelligence is transforming enterprises, Large Language Models (LLMs) are unlocking new frontiers in automation, augmentation, and intelligent decision-making. Ultimate Agentic AI with AutoGen for Enterprise Automation bridges the gap between foundational AI concepts and hands-on implementation, empowering professionals to build scalable and intelligent enterprise agents. The book begins with the core principles of LLM agents and gradually moves into advanced topics such as agent architecture, tool integration, memory systems, and context awareness. Readers will learn how to design task-specific agents, apply ethical and security guardrails, and operationalize them using the powerful AutoGen framework. Each chapter includes practical examplesfrom customer support to internal process automationensuring concepts are actionable in real-world settings. By the end of this book, you will have a comprehensive understanding of how to design, develop, deploy, and maintain LLM-powered agents tailored for enterprise needs. Whether youre a developer, data scientist, or enterprise architect, this guide offers a structured path to transform intelligent agent concepts into production-ready solutions. What you will learn Design and implement intelligent LLM agents using the AutoGen framework. Integrate external tools and APIs to enhance agent functionality. Fine-tune agent behavior for enterprise-specific use cases and goals. Deploy secure, scalable AI agents in real-world production environments. Monitor, evaluate, and maintain agents with robust operational strategies. Automate complex business workflows using enterprise-grade AI solutions.

Introducción. Mecánica. Electricidad (sistema eléctrico). Electrónica (sistemaelectrónico) (Interfaces de hardware). Interfaz para el puerto paralelo de las microcomputadoras XT mediante el circuito integrado 74HC688 (comparador de magnitud). Informatica (sistema informatico): control; la programacion informatica; interfaces comerciales; consideraciones basicas para el control; fallas mas frecuentes de los robots

Este libro reúne siete ensayos independientes, pero inspirados por una misma búsqueda: la de una mirada que tienda puentes entre tecnología y humanidades, con especial foco en el avance exponencial de la inteligencia artificial y en los problemas filosoficos que plantea. La inteligencia artificial esta alcanzando y superando fronteras hasta ahora reservadas a la ciencia ficcion. Su entrada en ambitos exclusivos de lo humano la creatividad, el lenguaje o la imaginacion abre un gran interrogante en torno a nuestra especie. La tecnologia es ya un asunto etico, filosofico y estetico. Por eso resulta cada vez mas necesaria la figura de humanistas capaces de sumarse al debate, no ya como invitados de cortesia, sino como protagonistas y expertos. Los siete ensayos de este volumen abordan la posibilidad y las condiciones de ese nuevo humanismo tecnologico desde diversos angulos: la importancia de la belleza como brujula en el diseño de la inteligencia artificial, los prejuicios entre tecnica y humanidades, la urgencia de diseñar un relato tecnologico alineado con intereses humanos, la creatividad artificial o la potencia artistica de las voces no humanas.

Debate interdisciplinar de gran altura sobre el libro de la bióloga y bioquímica Natalia López Moratalla "Inteligencia artifical, ¿conciencia artificial?: Una perspectiva desde las ciencias de la vida" (2017). Se tratan ante todo los avances neurocientificos de los ultimos años dsde el punto de vista de la autora y desde el antropologico, el juridico, el economico, el historico y varios mas. Sorprende que filosofos y antropologos sigan cultivando sus disciplinas sin asumir la necesidad de conocer lo que la neurociencia ha descubierto acerca de los asuntos que ellos estudian. Como contrapartida, sorprende tambien que una mayoria de neurocientificos saquen conclusiones propiamente antropologicas de lo que ven en el cerebro a traves del escaner, sin tener suficientes conocimientos de antropologia, ni cultural ni filosofica. Gran parte del debate se centra en este punto: en los conocimientos biogeneticos actuales, se ha observado que hay una frontera incluso fisiologica que solo traspasan, de hecho, los seres humanos y que se caracteriza porque se rige, paradojicamente, por la dinamica del caos y, por lo tanto, no se puede dominar en la medida necesaria para poder cambiarla con la seguridad de que el remedio no sea peor que la enfermedad. Pero tampoco se puede entender al ser humano sin tener en cuenta que, por debajo de ese umbral, los comportamientos humanos y animales se corresponden con una continua reorganizacion neuronal que puede expresarse matematicamente segun algoritmos.

El concepto de Big Data no solo hace referencia a grandes colecciones de datos, caracterizadas tanto por su volumen como por la variedad de formatos, sino que incluye también los sistemas y las tecnologias encargadas de almacenar, procesar y dar valor a toda esa informacion. La motivacion para gestionar y analizar estos datos surge de la evidencia de que el estudio de estos grandes volumenes permite adquirir un conocimiento que no es posible abordando solo conjuntos pequeños._x000D__x000D_De forma clara y didactica, el presente libro proporciona una idea panoramica y completa de los diferentes sistemas involucrados en el tratamiento del dato. _x000D_Esta vision general facilita al lector la comprension sencilla de los temas tratados, y proporciona el posicionamiento y la asimilacion de los distintos elementos que componen el ecosistema de tecnologias, servicios y soluciones de Big Data._x000D__x000D_Comenzando por las arquitecturas para la organizacion de la informacion, el libro se adentra en los sistemas para el almacenamiento y procesado del dato, llegando despues a las distintas formas de explotacion analitica: descriptiva, predictiva, prescriptiva y cognitiva. El gobierno del dato y la gestion de las distintas operaciones involucradas cierran este amplio e interesante recorrido._x000D__x000D_Los contenidos adaptados al Curso de Especializacion en Inteligencia Artificial y Big Data._x000D__x000D_

El presente libro tiene una clara vocación didáctica, se dirige a todas las personas que quieren adentrarse en el apasionante campo del aprendizaje automático combinando la teórica con la práctica para que sea sencillo asimilar las explicaciones._x000D__x000D_En esta obra se revisan los algoritmos mas comunes y su implementacion en Python. Comienza con una introduccion a las claves que han impulsado nuestra sociedad hacia la era de los datos y explora como, mediante tecnicas de aprendizaje automatico, obtener partido a la inmensa cantidad de datos que hoy nos rodea. A continuacion, se presenta el aprendizaje no supervisado con sus principales algoritmos y usos: agrupamiento, manifolds, reglas de asociacion y algoritmos de deteccion de anomalias. Le sigue el aprendizaje supervisado; partiendo del modelo mas simple, modelo lineal multivariante, se llega a las Maquinas de Soporte Vectorial (SVM). Finalmente, finaliza con el aprendizaje profundo (gran parte de lo que denominamos Inteligencia Artificial) donde se explican, de una manera sencilla e intuitiva, los perceptrones multicapa profundos, las redes convolucionales profundas (CNN) y los modelos recurrentes Long Short Term Memory (LSTM). _x000D__x000D_Esta obra contiene numerosas aplicaciones practicas con su codigo Python que podra descargar desde la web del libro._x000D__x000D_¿Te lo vas a perder?_x000D__x000D_El libro contiene material adicional que podra descargar accediendo a la ficha del libro en www.ra-ma.es._x000D__x000D_Los contenidos adaptados al Curso de Especializacion en Inteligencia Artificial y Big Data.

Un llamamiento inaplazable para poner freno a la carrera hacia la superinteligencia. «Un libro muy interesante, incluso si no estás de acuerdo con su conclusión.» Marta Peirano, periodista y escritor

Este libro surge a raíz de la necesidad de crear un compendio de prácticas para iniciar a alumnos de formación profesional de grado medio, grado superior y bachillerato a la robótica y a la domótica mediante la plataforma de Arduino._x000D_La estructura del libro permite diferenciar tres partes o bloques: el primero dedicado a exponer unos pocos conceptos sobre Arduino y las disciplinas que lo rodean; el segundo dedicado a la explicacion del lenguaje de programacion de Arduino; y el tercer bloque se dedica al aprendizaje de Arduino a traves de una serie de practicas, donde se expone un componente electronico o sensor._x000D_Cada practica posee el codigo totalmente explicado, comentado y analizado._x000D_Este libro propone una serie de 28 practicas detalladas y comentadas a docentes que deseen incorporar Arduino en alguna de sus asignaturas, y de guia de referencia y aprendizaje para aquellos lectores que puedan considerarse noveles en Arduino._x000D_Por tanto, el lector va aprendiendo mediante practicas, aisladas en apariencia, como manejar la placa Arduino para despues crear sus propios proyectos.

La creciente presencia de la inteligencia artificial (IA) en la sociedad es algo demasiado importante como para dejarlo solo en manos de ingenieros y filósofos, psicólogos y lingüistas, juristas y ne