Cargando…

Efficient processing of deep neural networks

Detalles Bibliográficos
Autores principales:	Sze, Vivienne, Chen, Yu-Hsin, Yang, Tien-Ju, Emer, Joel S
Lenguaje:	eng
Publicado:	Morgan & Claypool 2020
Materias:	Computing and Computers
Acceso en línea:	http://cds.cern.ch/record/2741465

Ejemplares similares

Deep learning for natural language processing: creating neural networks with Python
por: Goyal, Palash, et al.
Publicado: (2018)

Deep learning for natural language processing: solve your natural language processing problems with smart deep neural networks
por: Reddy Bokka, Karthiek, et al.
Publicado: (2019)

Embedded deep learning: algorithms, architectures and circuits for always-on neural network processing
por: Moons, Bert, et al.
Publicado: (2019)

Neural networks and deep learning
por: Géron, Aurélien
Publicado: (2018)

Optical signal processing, computing, and neural networks
por: Yu, Francis T S, et al.
Publicado: (1992)

Neural networks and deep learning: a textbook
por: Aggarwal, Charu C
Publicado: (2018)

Deep neural networks in a mathematical framework
por: Caterini, Anthony L, et al.
Publicado: (2018)

Deep neural networks: wasd neuronet models, algorithms, and applications
por: Zhang, Yunong, et al.
Publicado: (2019)

Neural network programming with TensorFlow: unleash the power of TensorFlow to train efficient neural networks
por: Ghotra, Manpreet Singh, et al.
Publicado: (2017)

Neural network methods in natural language processing
por: Goldberg, Yoav, et al.
Publicado: (2017)

Hands-on neural networks with Keras: design and create neural networks using deep learning and artificial intelligence principles
por: Purkait, Niloy
Publicado: (2019)

Keras deep learning cookbook: over 30 recipes for implementing deep neural networks in Python
por: Dua, Rajdeep, et al.
Publicado: (2018)

Deep learning essentials: your hands-on guide to the fundamentals of deep learning and neural network modeling
por: Di, Wei, et al.
Publicado: (2018)

Matlab deep learning: with machine learning, neural networks and artificial intelligence
por: Kim, Phil
Publicado: (2017)

Advanced applied deep learning: convolutional neural networks and object detection
por: Michelucci, Umberto
Publicado: (2019)

Learn Keras for deep neural networks: a fast-track approach to modern deep learning with Python
por: Moolayil, Jojo
Publicado: (2019)

Learn Keras for deep neural networks: a fast-track approach to modern deep learning with Python
por: Moolayil, Jojo
Publicado: (2018)

Evolutionary approach to machine learning and deep neural networks: neuro-evolution and gene regulatory networks
por: Iba, Hitoshi
Publicado: (2018)

Signal and image processing with neural networks: a C++ sourcebook
por: Masters, Timothy
Publicado: (1994)

Deep learning with Keras: implement neural networks with Keras on Theano and TensorFlow
por: Gulli, Antonio
Publicado: (2017)

Applied deep learning: a case-based approach to understanding neural networks
por: Michelucci, Umberto
Publicado: (2018)

Deep learning quick reference: useful hacks for training and optimizing deep neural networks with TensorFlow and Keras
por: Bernico, Michael
Publicado: (2018)

Python deep learning: exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow
por: Vasilev, Ivan
Publicado: (2019)

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

Practical convolutional neural networks: implement advanced deep learning models using Python
por: Sewak, Mohit, et al.
Publicado: (2018)

Deep learning with TensorFlow: explore neural networks and build intelligent systems with Python
por: Zaccone, Giancarlo, et al.
Publicado: (2018)

Deep neural network techniques in the calibration of space-charge distortion fluctuations for the ALICE TPC
por: Gorbunov, Sergey, et al.
Publicado: (2021)

Hands-on deep learning architectures with Python: create deep neural networks to solve computational problems using TensorFlow and Keras
por: Liu, Yuxi (Hayden), et al.
Publicado: (2019)

R deep learning projects: master the techniques to design and develop neural network models in R
por: Liu, Yuxi, et al.
Publicado: (2018)

Hands-on deep learning for IoT: train neural network models to develop intelligent IoT applications
por: Karim, Rezaul, et al.
Publicado: (2019)

Neural networks
por: Müller, Berndt, et al.
Publicado: (1990)

Neural networks
por: Amendolia, S R
Publicado: (1994)

Deep learning in natural language processing
por: Deng, Li, et al.
Publicado: (2018)

Hands-on deep learning for games: leverage the power of neural networks and reinforcement learning to build intelligent games
por: Lanham, Micheal
Publicado: (2019)

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

Deep learning by example: a hands-on guide to implementing advanced machine learning algorithms and neural networks
por: Menshawy, Ahmed
Publicado: (2018)

Artificial neural networks with Java: tools for building neural network applications
por: Livshin, Igor
Publicado: (2019)

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)

Hands-on deep learning with Go: a practical guide to building and implementing neural network models using Go
por: Seneque, Gareth, et al.
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_1c003q4uq7mi2t0kmp3r18r1o6