March 2025
Intermediate to advanced
352 pages
9h 37m
Spanish
Content preview from Web Scraping con Python, 3.ª edición
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Capítulo 12. Lectura y escritura de lenguas naturales
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Hasta ahora, los datos con los que has trabajado en este libro han sido en forma de números o valores contables. En la mayoría de los casos, te has limitado a almacenar los datos sin realizar ningún análisis a posteriori. Este capítulo pretende abordar el espinoso tema de la lengua inglesa.1
¿Cómo sabe Google lo que estás buscando cuando escribes "lindo gatito" en su buscador de imágenes? Por el texto que rodea a las imágenes de gatitos monos. ¿Cómo sabe YouTube que debe mostrar un sketch de los Monty Python cuando escribes "loro muerto" en su barra de búsqueda? Por el título y el texto descriptivo que acompañan a cada vídeo subido.
De hecho, incluso tecleando términos como "ave fallecida monty python" aparece inmediatamente el mismo sketch de "loro muerto", aunque la propia página no contenga ninguna mención a las palabras "fallecido" o "ave". Google sabe que un "perrito caliente" es un alimento y que un "perrito hirviendo" es una cosa totalmente distinta. ¿Cómo? ¡Es todo estadística!
Aunque quizá pienses que el análisis de texto no tiene nada que ver con tu proyecto, comprender los conceptos que lo sustentan puede ser extremadamente útil para todo tipo de aprendizaje automático, así como para la capacidad más general de modelar problemas del mundo real en términos probabilísticos y algorítmicos.
Por ejemplo, ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.