Cargando…

Deep learning with R /

Mostrar otras versiones (1)

Introduces deep learning systems using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples.

Detalles Bibliográficos
Clasificación:	Libro Electrónico
Autores principales:	Chollet, François (Autor), Allaire, J. J. (Autor)
Formato:	Electrónico eBook
Idioma:	Inglés
Publicado:	Shelter Island, NY : Manning Publications, [2018]
Temas:	R (Computer program language) Artificial intelligence. Neural networks (Computer science) Machine learning. Mathematical statistics > Data processing. Artificial Intelligence Neural Networks, Computer Machine Learning R (Langage de programmation) Intelligence artificielle. Réseaux neuronaux (Informatique) Apprentissage automatique. Statistique mathématique > Informatique. artificial intelligence. Artificial intelligence Machine learning Mathematical statistics > Data processing
Acceso en línea:	Texto completo (Requiere registro previo con correo institucional)

Ejemplares similares

Deep learning mit R und Keras : Das Praxis-Handbuch : von Entwicklern von Keras und RStudio /
por: Chollet, François, et al.
Publicado: (2018)

R deep learning essentials : a step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet /
por: Hodnett, Mark, et al.
Publicado: (2018)

Advanced deep learning with R : become an expert at designing, building, and improving advanced neural network models using R /
por: Rai, Bharatendra K.
Publicado: (2019)

R deep learning essentials : a step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet /
por: Hodnett, Mark, et al.
Publicado: (2018)

Advanced deep learning with R : become an expert at designing, building, and improving advanced neural network models using R /
por: Rai, Bharatendra K.
Publicado: (2019)

Advanced deep learning with R : become an expert at designing, building, and improving advanced neural network models using R /
por: Rai, Bharatendra K.
Publicado: (2019)

R deep learning cooking : solve complex neural net problems with TensorFlow, H2O and MXNet /
por: Prakash, PKS, et al.
Publicado: (2017)

Deep learning with R /
por: Chollet, François, et al.
Publicado: (2022)

Getting started with deep learning /
por: Patterson, Josh (Consultant), et al.
Publicado: (2018)

Python deep learning projects : 9 projects demystifying neural network and deep learning models for building intelligent systems /
por: Lamons, Matthew, et al.
Publicado: (2018)

Deep learning from scratch : building with Python from first principles /
por: Weidman, Seth
Publicado: (2019)

Advanced deep learning with TensorFlow 2 and Keras : apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more /
por: Atienza, Rowel
Publicado: (2020)

Deep learning with R in motion /
Publicado: (2019)

Deep learning shen du xue xi ji chu : she ji xia yi dai ren gong zhi hui yan suan fa = Fundamentals of deep learning : designing next-generation machine intelligence algorithms /
por: Buduma, Nikhil
Publicado: (2018)

Deep learning with PyTorch quick start guide : learn to train and deploy neural network models in Python /
por: Julian, David
Publicado: (2018)

Deep learning with PyTorch : a practical approach to building neural network models using PyTorch /
por: Subramanian, Vishnu
Publicado: (2018)

Deep learning with PyTorch : a practical approach to building neural network models using PyTorch /
por: Subramanian, Vishnu
Publicado: (2018)

ADVANCED DEEP LEARNING WITH TENSORFLOW 2 AND KERAS : APPLY DL, GANS, VAES, DEEP RL, UNSUPERVISED LEARNING, OBJECT DETECTION AND SEGMENTATION, AND MORE.
por: Atienza, Rowel
Publicado: (2020)

Deep Learning with TensorFlow 2 and Keras : Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition. /
por: Gulli, Antonio
Publicado: (2019)

Python shen du xue xi ru men : cong ling gou jian CNN he RNN = Deep learning from scratch /
por: Weidman, Seth
Publicado: (2021)

Neural networks with R : smart models using CNN, RNN, deep learning, and artificial intelligence principles /
por: Ciaburro, Giuseppe, et al.
Publicado: (2017)

Neural networks with R : smart models using CNN, RNN, deep learning, and artificial intelligence principles /
por: Ciaburro, Giuseppe, et al.
Publicado: (2017)

Deep learning with Microsoft Cognitive Toolkit quick start guide : a practical guide to building neural networks using Microsoft's open source deep learning framework /
por: Meints, Willem
Publicado: (2019)

Deep learning with Microsoft Cognitive Toolkit quick start guide : a practical guide to building neural networks using Microsoft's open source deep learning framework /
por: Meints, Willem
Publicado: (2019)

Hands-on generative adversarial networks with Keras : your guide to implementing next-generation generative adversarial networks /
por: Valle, Rafael, 1985-
Publicado: (2019)

R deep learning cookbook : solve complex neural net problems with TensorFlow, H2O and MXNet /
por: Prakash, PKS, Dr, et al.
Publicado: (2017)

R deep learning cookbook : solve complex neural net problems with TensorFlow, H2O and MXNet /
por: Prakash, PKS, Dr, et al.
Publicado: (2017)

Deep learning.
Publicado: (2023)

Deep learning.
Publicado: (2023)

Deep learning.
Publicado: (2023)

Artificial intelligence and machine learning fundamentals /
por: Nagy, Zsolt
Publicado: (2018)

Machine Learning Workshop - Second Edition /
por: Saleh, Hyatt
Publicado: (2020)

Advanced deep learning with Python.
por: Vasilev, Ivan
Publicado: (2019)

Advanced deep learning with Python.
por: Vasilev, Ivan
Publicado: (2019)

Deep Learning with PyTorch /
por: Antiga, Luca, et al.
Publicado: (2020)

Advanced deep learning with Python.
por: Vasilev, Ivan
Publicado: (2019)

The deep learning with PyTorch workshop.
por: Saleh, Hyatt
Publicado: (2020)

Deep Learning with Pytorch Quick Start Guide : Learn to Train and Deploy Neural Network Models in Python.
por: Julian, David
Publicado: (2018)

Advanced Deep Learning with Keras : Apply Deep Learning Techniques, Autoencoders, GANs, Variational Autoencoders, Deep Reinforcement Learning, Policy Gradients, and More.
por: Atienza, Rowel
Publicado: (2018)

Generative deep learning : teaching machines to paint, write, compose, and play /
por: Foster, David (Business consultant)
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_ri8o59roit742k1dtl5asamot6