{"title":"Computación","description":"","products":[{"product_id":"practical-machine-learning-for-computer-vision","title":"Practical machine learning for computer vision","description":"\u003cul class=\"a-unordered-list a-nostyle a-vertical a-spacing-none detail-bullet-list\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eEditorial ‏ : ‎\u003cspan\u003e \u003c\/span\u003e\u003c\/span\u003e\u003cspan\u003eO'Reilly Media\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eFecha de publicación ‏ : ‎\u003cspan\u003e \u003c\/span\u003e\u003c\/span\u003e\u003cspan\u003e24 Agosto 2021\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eEdición ‏ : ‎\u003cspan\u003e \u003c\/span\u003e\u003c\/span\u003e\u003cspan\u003ePrimera edición\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eIdioma ‏ : ‎\u003cspan\u003e \u003c\/span\u003e\u003c\/span\u003e\u003cspan\u003eInglés\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eNúmero de páginas ‏ : ‎\u003cspan\u003e \u003c\/span\u003e\u003c\/span\u003e\u003cspan\u003e480 páginas\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eISBN-10 ‏ : ‎\u003cspan\u003e \u003c\/span\u003e\u003c\/span\u003e\u003cspan\u003e1098102363\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eISBN-13 ‏ : ‎\u003cspan\u003e \u003c\/span\u003e\u003c\/span\u003e\u003cspan\u003e978-1098102364\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eEste libro práctico se presenta como una hoja de ruta indispensable para ingenieros de aprendizaje automático y científicos de datos que buscan dominar la extracción de información a partir de imágenes. Escrito por los expertos de Google Valliappa Lakshmanan, Martin Görner y Ryan Gillard, la obra ofrece un enfoque integral y aplicado para resolver desafíos del mundo real mediante técnicas avanzadas de visión por computadora. Los lectores encontrarán una guía detallada que abarca desde la creación y el preprocesamiento de conjuntos de datos hasta el diseño, entrenamiento y despliegue de modelos de alto rendimiento utilizando frameworks líderes como TensorFlow y Keras.\u003c\/p\u003e\n\u003cp\u003eA lo largo de sus páginas, el contenido profundiza en problemas críticos de la industria como la clasificación de imágenes, la detección de objetos, el uso de autoencoders y la generación de imágenes. El texto no solo se queda en la teoría, sino que enseña cómo poner estos modelos en producción a gran escala mediante arquitecturas robustas, flexibles y mantenibles. Además, se enfatizan aspectos fundamentales de la inteligencia artificial moderna, incluyendo la interpretabilidad de los modelos y las mejores prácticas para una IA responsable.\u003c\/p\u003e\n\u003cp\u003eEsta obra es el recurso ideal para técnicos especializados que desean actualizar sus conocimientos y aprender a construir canalizaciones de aprendizaje automático de extremo a extremo que sean precisas y explicables. Los autores comparten su experiencia directa en el desarrollo de sistemas complejos, proporcionando las herramientas necesarias para monitorear y gestionar modelos en entornos profesionales exigentes. Al adquirir este manual de la editorial O’Reilly Media, el lector accede a un conocimiento técnico de vanguardia que garantiza una ventaja competitiva en el sector tecnológico. Optimiza tus proyectos de visión artificial y lleva tus habilidades de ingeniería de datos al siguiente nivel con esta guía de referencia global.\u003c\/p\u003e\n\u003cdiv id=\"aplus_feature_div\" class=\"celwidget\" data-feature-name=\"aplus\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"aplus\" data-csa-c-slot-id=\"aplus_feature_div\" data-csa-c-asin=\"\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"a95zns-9x5rex-7hpwu5-j7da9e\" data-cel-widget=\"aplus_feature_div\"\u003e\n\u003cdiv id=\"aplus\" class=\"a-section a-spacing-large bucket\"\u003e\n\u003cdiv lang=\"en_US\"\u003e\n\u003cdiv class=\"aplus-v2 desktop celwidget\" data-csa-c-id=\"qh6zm1-14vn5w-hm0kz6-gech6n\" data-cel-widget=\"aplus\"\u003e\n\u003cdiv class=\"aplus-content-wrapper\"\u003e\n\u003cdiv class=\"celwidget aplus-module module-8 aplus-standard\" data-csa-c-id=\"835c2z-8kqz3b-2kspnr-esnuv8\" data-cel-widget=\"aplus-module-8\"\u003e\n\u003cdiv class=\"aplus-module-wrapper apm-fixed-width\"\u003e\n\u003cdiv class=\"apm-spacing\"\u003e\n\u003cdiv class=\"apm-lefttwothirdswrap apm-floatleft\"\u003e\n\u003cdiv class=\"apm-leftimage\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003cdiv class=\"apm-centerthirdcol\"\u003e\n\u003ch3 class=\"a-spacing-mini\"\u003e\u003cem\u003eFrom the Preface\u003c\/em\u003e\u003c\/h3\u003e\n\u003cp class=\"a-spacing-base\"\u003e\u003cem\u003eMachine learning on images is revolutionizing healthcare, manufacturing, retail, and many other sectors. Many previously difficult problems can now be solved by training machine learning (ML) models to identify objects in images. Our aim in this book is to provide intuitive explanations of the ML architectures that underpin this fast-advancing field, and to provide practical code to employ these ML models to solve problems involving classification, measurement, detection, segmentation, representation, generation, counting, and more.\u003c\/em\u003e\u003c\/p\u003e\n\u003cp class=\"a-spacing-base\"\u003e\u003cem\u003eImage classification is the “hello world” of deep learning. Therefore, this book also provides a practical end-to-end introduction to deep learning. It can serve as a stepping stone to other deep learning domains, such as natural language processing.\u003c\/em\u003e\u003c\/p\u003e\n\u003cp class=\"a-spacing-base\"\u003e\u003cem\u003eYou will learn how to design ML architectures for computer vision tasks and carry out model training using popular, well-tested prebuilt models written in TensorFlow and Keras. You will also learn techniques to improve accuracy and explainability. Finally, this book will teach you how to design, implement, and tune end-to-end ML pipelines for image understanding tasks.\u003c\/em\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"apm-rightthirdcol\"\u003e\n\u003cdiv class=\"apm-rightthirdcol-inner\"\u003e\n\u003ch4\u003e\u003cem\u003eThe Print format of this book is printed in black \u0026amp; white. See the Kindle format for a full color version.\u003c\/em\u003e\u003c\/h4\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"celwidget aplus-module basic-module-13-text aplus-standard\" data-csa-c-id=\"oligzj-v4ehet-x4k6bx-2k8ict\" data-cel-widget=\"aplus-basic-module-13-text\"\u003e\n\u003cdiv class=\"a-section a-spacing-none aplus-module aplus-module-13 aplus-module-wrapper apm-fixed-width\"\u003e\n\u003cdiv class=\"a-section a-spacing-none aplus-13-heading\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003cdiv class=\"a-section a-spacing-none aplus-module-section aplus-text-section\"\u003e\n\u003cp class=\"description\"\u003e\u003cem\u003e\u003cspan class=\"a-text-bold\"\u003eWho Is This Book For?\u003c\/span\u003e\u003c\/em\u003e\u003c\/p\u003e\n\u003cp class=\"description\"\u003e\u003cem\u003eThe primary audience for this book is software developers who want to do machine learning on images. It is meant for developers who will use TensorFlow and Keras to solve common computer vision use cases.\u003c\/em\u003e\u003c\/p\u003e\n\u003cp class=\"description\"\u003e\u003cem\u003eThe methods discussed in the book are accompanied by code samples available on GitHub. Most of this book involves open source TensorFlow and Keras and will work regardless of whether you run the code on premises, in Google Cloud, or in some other cloud.\u003c\/em\u003e\u003c\/p\u003e\n\u003cp class=\"description\"\u003e\u003cem\u003eDevelopers who wish to use PyTorch will find the textual explanations useful, but will probably have to look elsewhere for practical code snippets. We do welcome contributions of PyTorch equivalents of our code samples; please make a pull request to our GitHub repository.\u003c\/em\u003e\u003c\/p\u003e\n\u003cp class=\"description\"\u003e\u003cem\u003e\u003cspan class=\"a-text-bold\"\u003eHow To Use This Book\u003c\/span\u003e\u003c\/em\u003e\u003c\/p\u003e\n\u003cp class=\"description\"\u003e\u003cem\u003eWe recommend that you read this book in order. Make sure to read, understand, and run the accompanying notebooks in the book’s GitHub repository—you can run them in either Google Colab or Google Cloud’s Vertex Notebooks. We suggest that after reading each section of the text you try out the code to be sure you fully understand the concepts and techniques that are introduced. We strongly recommend completing the notebooks in each chapter before moving on to the next chapter.\u003c\/em\u003e\u003c\/p\u003e\n\u003cp class=\"description\"\u003e\u003cem\u003eGoogle Colab is free and will suffice to run most of the notebooks in this book; Vertex Notebooks is more powerful and so will help you run through the notebooks faster. The more complex models and larger datasets of Chapters 3, 4, 11, and 12 will benefit from the use of Google Cloud TPUs. Because all the code in this book is written using open source APIs, the code \u003cspan class=\"a-text-italic\"\u003eshould\u003c\/span\u003e also work in any other Jupyter environment where you have the latest version of TensorFlow installed, whether it’s your laptop, or Amazon Web Services (AWS) Sagemaker, or Azure ML. However, we haven’t tested it in those environments. If you find that you have to make any changes to get the code to work in some other environment, please do submit a pull request in order to help other readers.\u003c\/em\u003e\u003c\/p\u003e\n\u003cp class=\"description\"\u003e\u003cem\u003eThe code in this book is made available to you under an Apache open source license. It is meant primarily as a teaching tool, but can serve as a starting point for your production models.\u003c\/em\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv id=\"btfSubNavDesktopCopy\" class=\"celwidget\" data-feature-name=\"btfSubNavDesktop\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"btfSubNavDesktop\" data-csa-c-slot-id=\"btfSubNavDesktop_feature_div\" data-csa-c-asin=\"\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"oy2trn-et48cr-f01dqb-q74vtb\" data-cel-widget=\"btfSubNavDesktopCopy\"\u003e\u003c\/div\u003e\n\u003cdiv id=\"editorialReviews_feature_div\" class=\"celwidget\" data-feature-name=\"editorialReviews\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"editorialReviews\" data-csa-c-slot-id=\"editorialReviews_feature_div\" data-csa-c-asin=\"\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"9torxb-t4i56f-ee5of9-6wsbwn\" data-cel-widget=\"editorialReviews_feature_div\"\u003e\n\u003cdiv class=\"a-section a-spacing-small a-padding-base\"\u003e\n\u003ch3\u003e\u003cem\u003eAuthor\u003c\/em\u003e\u003c\/h3\u003e\n\u003cdiv class=\"a-section a-spacing-small a-padding-small\"\u003e\u003cem\u003eValliappa (Lak) Lakshmanan is the director of analytics and AI solutions at Google Cloud, where he leads a team building cross-industry solutions to business problems. His mission is to democratize machine learning so that it can be done by anyone anywhere.\u003cbr\u003e\u003cbr\u003eMartin Görner is a product manager for Keras\/TensorFlow focused on improving the developer experience when using state-of-the-art models. He's passionate about science, technology, coding, algorithms, and everything in between.\u003cbr\u003e\u003cbr\u003eRyan Gillard is an AI engineer in Google Cloud's Professional Services organization, where he builds ML models for a wide variety of industries. He started his career as a research scientist in the hospital and healthcare industry. With degrees in neuroscience and physics, he loves working at the intersection of those disciplines exploring intelligence through mathematics.\u003c\/em\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"O'Reilly Media, Inc.","offers":[{"title":"Nuevo","offer_id":48409218154737,"sku":"MLCVLAK9781098102364","price":85.0,"currency_code":"USD","in_stock":true},{"title":"Segunda mano","offer_id":48409218187505,"sku":"MLCVLAK9781098102365","price":65.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0734\/4180\/4529\/files\/81OAX7XZ9DL._SL1500.jpg?v=1784058826"}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0734\/4180\/4529\/collections\/81OAX7XZ9DL._SL1500.jpg?v=1784058917","url":"https:\/\/www.buholibreria.com\/collections\/computacion.oembed","provider":"Búho Cultura","version":"1.0","type":"link"}