Deep Learning / | Ian Goodfellow, Yoshua Bengio, Aaron Courville
Goodfellow, Ian
Deep Learning / Ian Goodfellow, Yoshua Bengio, Aaron Courville - Estados Unidos de América : MIT Press, 2016 - 775 p.; 23,5 x18 cm
Incluye índice
Applied math and machine learning basics. -- Linear algebra. -- Probability and information theory. -- Numerical Computation. -- Machine learning basics. -- Deep netwoks: modern practices. -- Regularization for deep learning. -- Optimization for training deep models. -- Convolutional Networks. -- Sequuence modeling: recurrent and recursive nets. -- Practical methodology. -- Applications. -- Deep learning research. -- Lineal factor models. -- Autoencoders. -- Representation learning. -- Structured probabilistic models for deep learning. -- Monte carlo methods. -- Confronting the partition fuction. -- Aproximate interference. -- Deep Generative models.
978-0-262-03561-3 (Pasta dura)
APRENDIZAJE AUTOMÁTICO
COMPUTADORAS Y TECNOLOGIAS DE LA INFORMACIÓN
ALGEBRA LINEAL
006.31 G651d 2016
Deep Learning / Ian Goodfellow, Yoshua Bengio, Aaron Courville - Estados Unidos de América : MIT Press, 2016 - 775 p.; 23,5 x18 cm
Incluye índice
Applied math and machine learning basics. -- Linear algebra. -- Probability and information theory. -- Numerical Computation. -- Machine learning basics. -- Deep netwoks: modern practices. -- Regularization for deep learning. -- Optimization for training deep models. -- Convolutional Networks. -- Sequuence modeling: recurrent and recursive nets. -- Practical methodology. -- Applications. -- Deep learning research. -- Lineal factor models. -- Autoencoders. -- Representation learning. -- Structured probabilistic models for deep learning. -- Monte carlo methods. -- Confronting the partition fuction. -- Aproximate interference. -- Deep Generative models.
978-0-262-03561-3 (Pasta dura)
APRENDIZAJE AUTOMÁTICO
COMPUTADORAS Y TECNOLOGIAS DE LA INFORMACIÓN
ALGEBRA LINEAL
006.31 G651d 2016