Loading…

Principles and labs for deep learning /

Bibliographic Details
Call Number:	Libro Electrónico
Main Author:	Huang, Shih-Chia
Other Authors:	Le, Trung-Hieu
Format:	Electronic eBook
Language:	Inglés
Published:	London : Academic Press, 2021.
Subjects:	Machine learning. Neural networks (Computer science) Neural Networks, Computer Machine Learning Apprentissage automatique. R�eseaux neuronaux (Informatique) Machine learning
Online Access:	Texto completo

Similar Items

Introduction to deep learning and neural networks with Python /
by: Gad, Ahmed, et al.
Published: (2020)

Artificial neural networks, 2 : proceedings of the 1992 International Conference on Artificial Neural Networks (ICANN-92), Brighton, United Kingdom, 4-7 September 1992 /
Published: (1992)

Handbook of neural computation /
Published: (2017)

Neural network modeling and identification of dynamical systems /
by: Tiumentsev, Yury V., et al.
Published: (2019)

Neural networks : advances and applications, 2 /
Published: (1992)

Deep learning with fastai cookbook leverage the easy-to-use fastai framework to unlock the power of deep learning /
by: Ryan, Mark
Published: (2021)

Memristive devices for brain-inspired computing : from materials, devices, and circuits to applications : computational memory, deep learning, and spiking neural networks /
Published: (2020)

Generative adversarial networks for image-to-image translation /
Published: (2021)

Neural networks for perception /
Published: (1992)

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

Neural networks with Keras cookbook : over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots /
by: Ayyadevara, V. Kishore
Published: (2019)

Kohonen maps /
Published: (1999)

Hands-on neural networks with TensorFlow 2.0 : train, model and deploy the neural networks into your systems using the power of TensorFlow 2.0 /
by: Galeone, Paolo
Published: (2019)

Semi-Empirical Neural Network Modeling and Digital Twins Development /
by: Tarkhov, Dmitriy
Published: (2020)

Deep learning patterns and practices /
by: Ferlitsch, Andrew
Published: (2021)

Conformal prediction for reliable machine learning : theory, adaptations, and applications /
Published: (2014)

Single neuron computation /
Published: (1992)

Introduction to deep learning : concepts and fundamentals /
Published: (2017)

Introduction to neural networks.
Published: (1991)

Keras 2.x projects : 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras /
by: Ciaburro, Giuseppe
Published: (2018)

A guide to neural computing applications /
by: Tarassenko, Lionel
Published: (1998)

Computational neural networks for geophysical data processing /
Published: (2001)

Deep learning : a visual approach /
by: Glassner, Andrew S.
Published: (2021)

Live-coding a machine learning model from scratch /
Published: (2019)

Deep neural networks and applications
by: Stanimirović, Ivan
Published: (2020)

Theoretical mechanics of biological neural networks /
by: MacGregor, Ronald J.
Published: (1993)

Deep learning patterns and practices /
by: Ferlitsch, Andrew
Published: (2021)

Deep learning projects using TensorFlow 2 : neural network development with Python and Keras /
by: Silaparasetty, Vinita
Published: (2020)

Artificial neural networks with TensorFlow 2 : ANN architecture machine learning projects /
by: Sarang, P. G. (Poornachandra G.)
Published: (2021)

Thinking machines : machine learning and its hardware implementation /
by: Takano, Shigeyuki
Published: (2021)

State of the art in neural networks and their applications.
Published: (2021)

The TensorFlow Workshop /
by: Moocarme, Matthew, et al.
Published: (2021)

Deep learning with TensorFlow /
Published: (2018)

Playing with GANs : building, coding, and modifying deep learning GAN models.
Published: (2021)

Introduction to computer vision with TensorFlow : using convolutional neural networks and TensorFlow to solve computer vision tasks /
Published: (2017)

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

Generative adversarial networks projects : build next-generation generative models using TensorFlow and Keras /
by: Ahirwar, Kailash
Published: (2019)

Neural networks modeling and control : applications for unknown nonlinear delayed systems in discrete time /
by: Rios, Jorge D.
Published: (2020)

Generative Adversarial Networks Projects : Build Next-Generation Generative Models Using TensorFlow and Keras.
by: Ahirwar, Kailash
Published: (2019)

Advances in domain adaptation theory /
by: Redko, Ievgen, et al.
Published: (2019)

Cannot write session to /tmp/vufind_sessions/sess_g11js8hq5f3soom1hom93eff7f