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Aprendizaje automático profundo: GuÃa completa para desarrolladores para principiantes sobre algoritmos, conceptos y técnicas de aprendizaje automátic
Paperback
Series: Aprendizaje Automático Profundo, Book 1
Publisher Price: $19.99
Publisher: Joe Grant
Published: Nov 24 2023
Pages: 152
Weight: 0.47
Height: 0.33 Width: 6.00 Depth: 9.00
Language: Spanish
Está interesado en el Aprendizaje Automatico? Te fascina cómo funcionan los robots? Estás listo para abrirte a la dinámica del cambio tecnológico?
El aprendizaje automático se ha abordado de manera definitiva como un subconjunto que cae bajo un conjunto más grande de inteligencia artificial. Se centra principalmente en el aspecto del aprendizaje de máquinas basándose en la experiencia y la predicción de las consecuencias y acciones de las máquinas que giran en torno a su experiencia en el pasado.
El campo ha hecho que sea fácil para los equipos y máquinas promulgar decisiones basadas en datos en lugar de programación explÃcita con respecto a una tarea en particular. Los algoritmos y programas están diseñados para permitir que las máquinas y computadoras aprendan por sà mismos. Con el tiempo, pueden mejorar cuando hay una introducción de datos nuevos y únicos. El proceso de aprendizaje incluyeel uso de datos de formación quesostienen la aparición de un modelo. La inserción de nuevos datos muestra predicciones basadas en el modelo. Esto significa que las máquinas tienen la capacidad de prever por sà solas.
A continuación, las predicciones se examinan detenidamente para identificar su exactitud. Si la precisión recibe comentarios positivos, el algoritmo de aprendizaje automático se entrena una y otra vez a través de la ayuda de un conjunto aumentado de entrenamiento de datos.
Las tareas de aprendizaje automático se dividen en varias categorÃas más amplias. El aprendizaje supervisado tiene como objetivo elaborar un modelo que sea matemáticode un conjunto de datos con las entradas y salidas deseadas. Semi-supervisadolearning tiene como objetivo llegar a modelos matemáticos de entrenamiento de datos incompleto. Se dará cuenta de que las entradas de muestra no se necesitan/desean la salida en tal caso.
Este libro le ayudará a comprender mejor el aprendizaje automático profundo. En las páginas de este libro, usted será capaz de obtener capÃtulos importantes que incluyen:
- Historia del aprendizaje automatizado
- Los beneficios
- Los desafÃos que puede encontrar
- Aplicaciones del aprendizaje automatico
- Inteligencia Artificial
- Big Data
- Y mucho más!
Con ese conocimiento, usted será capaz de abrazar los avances tecnológicos y estar listo para el futuro.
Obtener una copia de Deep Machine Learning hoy y llegar a descubrir los secretos en la tecnologÃa!
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