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271407897
Aprende Machine Learning con Scikit-Learn, Keras y TensorFlow. Tercera Edición: Conceptos, herramientas y técnicas para conseguir sistemas
Item #:
271407897
PYG 841634
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- Gracias a varios logros innovadores, el deep learning ha dado un gran impulso a todo el campo del machine learning. Ahora, incluso programadores que no saben casi nada de esta tecnología pueden usar herramientas sencillas y eficaces para implementar programas capaces de aprender a partir de datos. Este best seller utiliza ejemplos concretos, una teoría mínima y frameworks de Python listos para la producción (Scikit Learn, Keras y TensorFlow) para ayudarte a obtener una comprensión intuitiva de los conceptos y herramientas para crear sistemas inteligentes.Con esta tercera edición actualizada, el autor Aurélien Géron explora una variedad de técnicas que van desde una regresión lineal simple a redes neuronales profundas. Hay ejemplos de código y ejercicios por todo el libro para ayudarte a aplicar lo que has aprendido, lo único que necesitas para empezar es experiencia en programación:* Utiliza Scikit-Learn para hacer un seguimiento de un proyecto de machine learning de ejemplo de principio a fin.* Explora varios modelos, incluyendo máquinas de vectores soporte, árboles de decisión, random forests y métodos de ensamblaje.* Aprovecha técnicas de aprendizaje no supervisado, como la reducción de dimensionalidad, el agrupamiento y la detección de anomalías.* Sumérgete en arquitecturas de redes neuronales, incluyendo redes convolucionales, redes recurrentes, redes generativas antagónicas, autocodificadores, modelos de difusión y transformadores.* Utiliza TensorFlow y Keras para crear y entrenar redes neuronales para visión por ordenador, procesamiento del lenguaje natural, modelos generativos y aprendizaje profundo por refuerzo.
| Publisher | ANAYA MULTIMEDIA |
| Publication date | 15 Jun. 2023 |
| Edition | edition |
| Language | Spanish |
| Print length | 832 pages |
| ISBN-10 | 8441548048 |
| ISBN-13 | 978-8441548046 |
| Item weight | 1.33 kg |
| Dimensions | 18 x 4.8 x 22.5 cm |
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- Ideal para programadores sin experiencia previa en Machine Learning.
- Incluye ejemplos prácticos y código listo para producción.
- Cubre técnicas desde regresiones simples hasta redes neuronales profundas.
- Explora modelos como máquinas de vectores soporte y árboles de decisión.
- Incorpora técnicas de aprendizaje no supervisado y redes neuronales avanzadas.
- Actualizado a la tercera edición con los últimos avances en deep learning.
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