R deep learning essentials : a step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet /

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This book demonstrates how to use deep Learning in R for machine learning, image classification, and natural language processing. It covers topics such as convolutional networks, recurrent neural networks, transfer learning and deep learning in the cloud. By the end of this book, you will be able to...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Hodnett, Mark (Autor), Wiley, Joshua F. (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham : Packt Publishing Ltd, 2018.
Edición:Second edition.
Temas:
R (Computer program language)
Artificial intelligence.
Machine learning.
Neural networks (Computer science)
Artificial Intelligence
Neural Networks, Computer
Machine Learning
R (Langage de programmation)
Intelligence artificielle.
Apprentissage automatique.
Réseaux neuronaux (Informatique)
artificial intelligence.
MATHEMATICS > Applied.
MATHEMATICS > Probability & Statistics > General.
Artificial intelligence
Machine learning
Acceso en línea:Texto completo
Descripción
Sumario:This book demonstrates how to use deep Learning in R for machine learning, image classification, and natural language processing. It covers topics such as convolutional networks, recurrent neural networks, transfer learning and deep learning in the cloud. By the end of this book, you will be able to apply deep learning to real-world projects.
Notas:Includes index.
Document classification.
Descripción Física:1 online resource
ISBN:9781788997805
1788997808

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