{"id":177151,"date":"2025-02-05T07:30:00","date_gmt":"2025-02-05T06:30:00","guid":{"rendered":"https:\/\/datascientest.com\/es\/?p=177151"},"modified":"2025-01-31T15:40:08","modified_gmt":"2025-01-31T14:40:08","slug":"tensorflow-extended-tfx-que-es","status":"publish","type":"post","link":"https:\/\/datascientest.com\/es\/tensorflow-extended-tfx-que-es","title":{"rendered":"TensorFlow Extended (TFX): \u00bfQu\u00e9 es? \u00bfC\u00f3mo se utiliza?"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"177151\" class=\"elementor elementor-177151\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-3bde660 e-flex e-con-boxed e-con\" data-id=\"3bde660\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1dd6c9b elementor-widget elementor-widget-text-editor\" data-id=\"1dd6c9b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><b>TensorFlow Extended (TFX) es una plataforma robusta desarrollada por Google dise\u00f1ada para estandardizar y optimizar todo el ciclo de vida de los modelos de machine learning (ML).<\/b><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3332dd6 elementor-widget elementor-widget-text-editor\" data-id=\"3332dd6\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Con sus numerosos componentes y sus integraciones avanzadas, TFX permite a las empresas construir <\/span><b>pipelines automatizados y escalables<\/b><span style=\"font-weight: 400;\">, asegurando al mismo tiempo la calidad y la trazabilidad de los procesos. En este art\u00edculo, exploramos en profundidad las funcionalidades de TFX, sus aplicaciones y las razones por las que constituye una soluci\u00f3n de elecci\u00f3n para los proyectos ML complejos.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9980126 e-flex e-con-boxed e-con\" data-id=\"9980126\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-71da47f elementor-widget elementor-widget-heading\" data-id=\"71da47f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h3 class=\"elementor-heading-title elementor-size-default\">\u00bfQu\u00e9 es TensorFlow Extended (TFX)?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-016d8ec elementor-widget elementor-widget-text-editor\" data-id=\"016d8ec\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><b>TFX<\/b><span style=\"font-weight: 400;\"> es una plataforma open source construida alrededor de TensorFlow, destinada a industrializar el ciclo de vida de los modelos de aprendizaje autom\u00e1tico. El objetivo principal de TFX es hacer que los pipelines ML sean m\u00e1s eficaces <\/span><b>automatizando las tareas clave del ML<\/b><span style=\"font-weight: 400;\">, como la preparaci\u00f3n de datos, el entrenamiento y el despliegue de los modelos, minimizando al mismo tiempo las intervenciones humanas.<\/span><\/p><p><span style=\"font-weight: 400;\">Gracias a sus integraciones con herramientas como <\/span><b>Apache Beam<\/b><span style=\"font-weight: 400;\">, <\/span><a href=\"https:\/\/datascientest.com\/es\/todo-sobre-apache-airflow\"><span style=\"font-weight: 400;\">Apache Airflow<\/span><\/a><span style=\"font-weight: 400;\"> y <\/span><b>Kubeflow Pipelines<\/b><span style=\"font-weight: 400;\">, TFX se adapta tanto a los entornos cloud como a las infraestructuras locales, ofreciendo as\u00ed una flexibilidad inigualable.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9bd2ff9 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"9bd2ff9\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/datascientest.com\/es\/nuestros-cursos-de-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">M\u00e1s informaci\u00f3n sobre TensorFlow Extended<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-af8ae55 e-flex e-con-boxed e-con\" data-id=\"af8ae55\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2206fd4 elementor-widget elementor-widget-heading\" data-id=\"2206fd4\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Los componentes clave de TFX: una plataforma modular<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d01a720 elementor-widget elementor-widget-text-editor\" data-id=\"d01a720\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Los componentes de TFX son el coraz\u00f3n de su eficacia. Cada uno desempe\u00f1a un papel espec\u00edfico en la creaci\u00f3n y gesti\u00f3n de los pipelines ML.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4315745 elementor-widget elementor-widget-heading\" data-id=\"4315745\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">1. TensorFlow Data Validation (TFDV)<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8cc2cf9 elementor-widget elementor-widget-text-editor\" data-id=\"8cc2cf9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><b>TFDV<\/b><span style=\"font-weight: 400;\"> est\u00e1 dise\u00f1ado para analizar los conjuntos de datos y detectar anomal\u00edas o incoherencias. Ofrece visualizaciones ricas y estad\u00edsticas detalladas, permitiendo asegurar que los datos de entrada cumplen con los est\u00e1ndares requeridos para el entrenamiento de los modelos.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2f74815 elementor-widget elementor-widget-image\" data-id=\"2f74815\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1000\" height=\"571\" src=\"https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-1.webp\" class=\"attachment-full size-full wp-image-177156\" alt=\"\" srcset=\"https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-1.webp 1000w, https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-1-300x171.webp 300w, https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-1-768x439.webp 768w\" sizes=\"(max-width: 1000px) 100vw, 1000px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8162af2 elementor-widget elementor-widget-heading\" data-id=\"8162af2\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">2. TensorFlow Transform (TFT)<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-680d1d7 elementor-widget elementor-widget-text-editor\" data-id=\"680d1d7\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><b>TFT<\/b><span style=\"font-weight: 400;\"> es una herramienta poderosa para aplicar transformaciones escalables a los datos, como la normalizaci\u00f3n o la codificaci\u00f3n categ\u00f3rica. Estas transformaciones se registran y aplican de manera coherente durante el entrenamiento y la predicci\u00f3n.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a20fb17 elementor-widget elementor-widget-heading\" data-id=\"a20fb17\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">3. TensorFlow Model Analysis (TFMA)<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4cc59f4 elementor-widget elementor-widget-text-editor\" data-id=\"4cc59f4\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Con <\/span><b>TFMA<\/b><span style=\"font-weight: 400;\">, se puede analizar y evaluar los modelos utilizando m\u00e9tricas adaptadas a los objetivos. Tambi\u00e9n facilita la identificaci\u00f3n de sesgos y debilidades en el rendimiento de los modelos.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cb3f6a6 elementor-widget elementor-widget-heading\" data-id=\"cb3f6a6\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">4. TensorFlow Serving<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3bbb139 elementor-widget elementor-widget-text-editor\" data-id=\"3bbb139\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Este componente gestiona el despliegue de los modelos en producci\u00f3n. Est\u00e1 optimizado para proporcionar predicciones en tiempo real y soporta actualizaciones continuas sin interrupci\u00f3n de los servicios.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bb9f633 elementor-widget elementor-widget-heading\" data-id=\"bb9f633\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">5. ML Metadata (MLMD)<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a04896e elementor-widget elementor-widget-text-editor\" data-id=\"a04896e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><b>MLMD<\/b><span style=\"font-weight: 400;\"> asegura una <\/span><b>gesti\u00f3n centralizada<\/b><span style=\"font-weight: 400;\"> de los metadatos generados por los pipelines. Esto incluye informaci\u00f3n sobre las transformaciones, los hiperpar\u00e1metros y los resultados de los modelos, permitiendo una trazabilidad total.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3434d33 elementor-widget elementor-widget-heading\" data-id=\"3434d33\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">6. TensorFlow Pipeline Orchestration<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-47b5705 elementor-widget elementor-widget-text-editor\" data-id=\"47b5705\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><b>TFX<\/b><span style=\"font-weight: 400;\"> soporta herramientas de orquestaci\u00f3n como Apache Airflow y Kubeflow Pipelines, que automatizan la ejecuci\u00f3n de los pipelines, ofreciendo as\u00ed una gesti\u00f3n fluida de las tareas y una escalabilidad aumentada.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e0e5724 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"e0e5724\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/datascientest.com\/es\/nuestros-cursos-de-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Dominar los componentes clave del TFX<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-276a573 e-flex e-con-boxed e-con\" data-id=\"276a573\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9fe030e elementor-widget elementor-widget-heading\" data-id=\"9fe030e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">\u00bfPor qu\u00e9 adoptar TFX para tus proyectos ML?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-84360d4 elementor-widget elementor-widget-heading\" data-id=\"84360d4\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">1. Automatizaci\u00f3n y ahorro de tiempo<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bcfc625 elementor-widget elementor-widget-text-editor\" data-id=\"bcfc625\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Con TFX, las tareas recurrentes como la <\/span><b>validaci\u00f3n de datos<\/b><span style=\"font-weight: 400;\"> o la <\/span><b>evaluaci\u00f3n de modelos est\u00e1n automatizadas<\/b><span style=\"font-weight: 400;\">, permitiendo as\u00ed a los equipos centrarse en aspectos estrat\u00e9gicos. Los procesos automatizados tambi\u00e9n reducen los riesgos de errores humanos.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bd6c100 elementor-widget elementor-widget-heading\" data-id=\"bd6c100\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">2. Integraci\u00f3n transparente<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3d5e410 elementor-widget elementor-widget-text-editor\" data-id=\"3d5e410\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">TFX se integra perfectamente con los entornos existentes, ya sean basados en la nube o locales. Las empresas pueden aprovechar las soluciones cloud como Google Cloud o herramientas como <\/span><b>Vertex AI<\/b><span style=\"font-weight: 400;\"> para reforzar sus capacidades de procesamiento.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-886cb56 elementor-widget elementor-widget-heading\" data-id=\"886cb56\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">3. Estandardizaci\u00f3n y reproducibilidad<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c7f3b92 elementor-widget elementor-widget-text-editor\" data-id=\"c7f3b92\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Los pipelines TFX est\u00e1n dise\u00f1ados para ser <\/span><b>estandardizados<\/b><span style=\"font-weight: 400;\"> y <\/span><b>reproducibles<\/b><span style=\"font-weight: 400;\">, garantizando una coherencia en el procesamiento de los datos y el entrenamiento de los modelos.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e5ebedb elementor-widget elementor-widget-heading\" data-id=\"e5ebedb\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">4. Optimizaci\u00f3n de costos<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6719128 elementor-widget elementor-widget-text-editor\" data-id=\"6719128\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Gracias a una orquestaci\u00f3n eficaz y a la automatizaci\u00f3n, TFX reduce el tiempo y los recursos necesarios para poner modelos en producci\u00f3n.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7870a80 elementor-widget elementor-widget-image\" data-id=\"7870a80\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1000\" height=\"571\" src=\"https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-2.webp\" class=\"attachment-full size-full wp-image-177155\" alt=\"\" srcset=\"https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-2.webp 1000w, https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-2-300x171.webp 300w, https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-2-768x439.webp 768w\" sizes=\"(max-width: 1000px) 100vw, 1000px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-e2cad14 e-flex e-con-boxed e-con\" data-id=\"e2cad14\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-349f609 elementor-widget elementor-widget-heading\" data-id=\"349f609\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Aplicaciones industriales de TFX<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cec9b55 elementor-widget elementor-widget-text-editor\" data-id=\"cec9b55\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">TFX se adapta a una gran variedad de sectores gracias a su flexibilidad y sus funcionalidades avanzadas. Aqu\u00ed tienes algunos ejemplos de aplicaciones concretas:<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9d407e1 elementor-widget elementor-widget-heading\" data-id=\"9d407e1\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">1. Sector del e-commerce<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5a6b433 elementor-widget elementor-widget-text-editor\" data-id=\"5a6b433\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Las empresas utilizan <\/span><b>TFX<\/b><span style=\"font-weight: 400;\"> para optimizar los sistemas de recomendaci\u00f3n, permitiendo una personalizaci\u00f3n aumentada de la experiencia del usuario basada en los comportamientos de los clientes.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5326f6e elementor-widget elementor-widget-heading\" data-id=\"5326f6e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">2. Salud y biotecnolog\u00eda<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c966beb elementor-widget elementor-widget-text-editor\" data-id=\"c966beb\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">TFX facilita el an\u00e1lisis de datos m\u00e9dicos voluminosos, contribuyendo a avances en los diagn\u00f3sticos asistidos por inteligencia artificial.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3bea171 elementor-widget elementor-widget-heading\" data-id=\"3bea171\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">3. Servicios financieros<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f50ff21 elementor-widget elementor-widget-text-editor\" data-id=\"f50ff21\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Las instituciones financieras se apoyan en TFX para aplicaciones cr\u00edticas como la detecci\u00f3n de fraudes o la evaluaci\u00f3n de riesgos, donde la precisi\u00f3n y la rapidez son primordiales.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-78eb7cf elementor-widget elementor-widget-heading\" data-id=\"78eb7cf\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">4. Publicidad digital<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-97d3c70 elementor-widget elementor-widget-text-editor\" data-id=\"97d3c70\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">En el \u00e1mbito del marketing digital, TFX se utiliza para optimizar las campa\u00f1as publicitarias analizando los datos de los usuarios en tiempo real gracias a <\/span><b>TensorFlow Serving<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4fa977c elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"4fa977c\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/datascientest.com\/es\/nuestros-cursos-de-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Aprenda a utilizar TFX para sus proyectos de IA<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-69cb17a e-flex e-con-boxed e-con\" data-id=\"69cb17a\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5dd7d39 elementor-widget elementor-widget-heading\" data-id=\"5dd7d39\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Pasos pr\u00e1cticos para crear un pipeline ML con TFX<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5a21215 elementor-widget elementor-widget-text-editor\" data-id=\"5a21215\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ol><li style=\"font-weight: 400;\" aria-level=\"1\"><b>An\u00e1lisis de datos:<\/b><span style=\"font-weight: 400;\"> Utiliza TFDV para inspeccionar los datos e identificar las anomal\u00edas potenciales.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Transformaci\u00f3n de datos:<\/b><span style=\"font-weight: 400;\"> Aplica transformaciones escalables a trav\u00e9s de TFT.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Entrenamiento de modelos:<\/b><span style=\"font-weight: 400;\"> Configura tus algoritmos con TensorFlow para aprender a partir de los datos transformados.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Evaluaci\u00f3n del rendimiento:<\/b><span style=\"font-weight: 400;\"> Verifica la eficacia de los modelos con TFMA.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Puesta en producci\u00f3n:<\/b><span style=\"font-weight: 400;\"> Despliega los modelos utilizando TensorFlow Serving.<\/span><\/li><li><b>Monitoreo continuo:<\/b><span style=\"font-weight: 400;\"> Usa MLMD para seguir el rendimiento y ajustar los modelos si es necesario.<\/span><\/li><\/ol>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f702044 elementor-widget elementor-widget-image\" data-id=\"f702044\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1000\" height=\"571\" src=\"https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-3.webp\" class=\"attachment-full size-full wp-image-177154\" alt=\"\" srcset=\"https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-3.webp 1000w, https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-3-300x171.webp 300w, https:\/\/datascientest.com\/es\/files\/2025\/01\/TensorFlow-Extended-TFX-DataScientest-3-768x439.webp 768w\" sizes=\"(max-width: 1000px) 100vw, 1000px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-45c0907 e-flex e-con-boxed e-con\" data-id=\"45c0907\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-928de75 elementor-widget elementor-widget-heading\" data-id=\"928de75\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Desaf\u00edos comunes y soluciones aportadas por TFX<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f993028 elementor-widget elementor-widget-heading\" data-id=\"f993028\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">Complejidad de los sistemas ML<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-621b12d elementor-widget elementor-widget-text-editor\" data-id=\"621b12d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">TFX simplifica la construcci\u00f3n y gesti\u00f3n de los pipelines unificando las etapas cr\u00edticas en una sola plataforma.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-76087e0 elementor-widget elementor-widget-heading\" data-id=\"76087e0\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">Mantenimiento continuo<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-00ffd9a elementor-widget elementor-widget-text-editor\" data-id=\"00ffd9a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">El monitoreo y reentrenamiento automatizados aseguran que los modelos se mantengan eficaces frente a las evoluciones de los datos.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ab2f072 elementor-widget elementor-widget-heading\" data-id=\"ab2f072\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\"><font size=\"4\">Gesti\u00f3n de recursos<\/font><\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f0c9da4 elementor-widget elementor-widget-text-editor\" data-id=\"f0c9da4\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Al integrar soluciones cloud y herramientas de orquestaci\u00f3n, TFX permite optimizar el uso de recursos y reducir los costos.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-5a081a8 e-flex e-con-boxed e-con\" data-id=\"5a081a8\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-267e768 elementor-widget elementor-widget-heading\" data-id=\"267e768\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Conclusi\u00f3n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e05f652 elementor-widget elementor-widget-text-editor\" data-id=\"e05f652\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><b>TensorFlow Extended (TFX)<\/b><span style=\"font-weight: 400;\"> es una herramienta imprescindible para las empresas que buscan <\/span><a href=\"https:\/\/datascientest.com\/es\/pipeline-definicion-funcionamiento-y-uso-en-data-science\"><span style=\"font-weight: 400;\">maximizar la eficacia y la fiabilidad de sus pipelines ML<\/span><\/a><span style=\"font-weight: 400;\">. Gracias a sus componentes modulares y sus capacidades de integraci\u00f3n, ofrece una soluci\u00f3n completa para <\/span><b>automatizar<\/b><span style=\"font-weight: 400;\"> y <\/span><b>estandardizar<\/b><span style=\"font-weight: 400;\"> el ciclo de vida de los modelos ML. Ya seas un desarrollador o un tomador de decisiones, invertir en TFX es una decisi\u00f3n estrat\u00e9gica para <a href=\"https:\/\/datascientest.com\/formation-intelligence-artificielle\">asegurar el \u00e9xito a largo plazo de tus proyectos de inteligencia artificial<\/a>.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c1d2754 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"c1d2754\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/datascientest.com\/es\/nuestros-cursos-de-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Realice un curso de formaci\u00f3n con DataScientest<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7eaa4a5 e-flex e-con-boxed e-con\" data-id=\"7eaa4a5\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4a4e6c0 elementor-widget elementor-widget-html\" data-id=\"4a4e6c0\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\r\n{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"FAQPage\",\r\n  \"mainEntity\": [\r\n    {\r\n      \"@type\": \"Question\",\r\n      \"name\": \"\u00bfQu\u00e9 es TensorFlow Extended (TFX)?\",\r\n      \"acceptedAnswer\": {\r\n        \"@type\": \"Answer\",\r\n        \"text\": \"TensorFlow Extended (TFX) es una plataforma de c\u00f3digo abierto dise\u00f1ada para la gesti\u00f3n completa de pipelines de machine learning, desde la preparaci\u00f3n de datos hasta el despliegue de modelos en producci\u00f3n.\"\r\n      }\r\n    },\r\n    {\r\n      \"@type\": \"Question\",\r\n      \"name\": \"\u00bfCu\u00e1les son los componentes clave de TFX?\",\r\n      \"acceptedAnswer\": {\r\n        \"@type\": \"Answer\",\r\n        \"text\": \"Los componentes clave de TFX incluyen TFX Data Validation (TFDV) para el an\u00e1lisis de datos, TensorFlow Transform (TFT) para la transformaci\u00f3n de datos, TensorFlow Model Analysis (TFMA) para la evaluaci\u00f3n de modelos y TensorFlow Serving para el despliegue en producci\u00f3n.\"\r\n      }\r\n    },\r\n    {\r\n      \"@type\": \"Question\",\r\n      \"name\": \"\u00bfCu\u00e1les son las ventajas de TFX en comparaci\u00f3n con otras plataformas de machine learning?\",\r\n      \"acceptedAnswer\": {\r\n        \"@type\": \"Answer\",\r\n        \"text\": \"TFX est\u00e1 estrechamente integrado con TensorFlow, lo que permite una gesti\u00f3n fluida de los modelos. 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Con sus numerosos componentes y sus integraciones avanzadas, TFX permite a las empresas construir pipelines automatizados y escalables, asegurando al mismo tiempo la calidad y la trazabilidad de [&hellip;]<\/p>\n","protected":false},"author":45,"featured_media":177153,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2427],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>TensorFlow Extended (TFX): \u00bfQu\u00e9 es? \u00bfC\u00f3mo se utiliza?<\/title>\n<meta name=\"description\" content=\"Descubre TensorFlow Extended (TFX), el marco de c\u00f3digo abierto de Google para implementar pipelines de machine learning en producci\u00f3n: automatizaci\u00f3n, escalabilidad y gesti\u00f3n optimizada de modelos.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/es\/tensorflow-extended-tfx-que-es\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"TensorFlow Extended (TFX): \u00bfQu\u00e9 es? 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