Cargando…

Advanced deep learning with Keras: apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more

Detalles Bibliográficos
Autor principal:	Atienza, Rowel
Lenguaje:	eng
Publicado:	Packt Publishing 2018
Materias:	Computing and Computers
Acceso en línea:	http://cds.cern.ch/record/2653256

Ejemplares similares

Applied deep learning with Keras: solve complex real-life problems with the simplicity of Keras
por: Bhagwat, Ritesh, et al.
Publicado: (2019)

Advanced Deep Learning with TensorFlow 2 and Keras
por: Atienza, Rowel
Publicado: (2020)

Pytorch deep learning hands-on: apply modern AI techniques with CNNS, RNNS, GANs, reinforcement learning, and more
por: Thomas, Sherin, et al.
Publicado: (2019)

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

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)

Deep learning in TMVA Benchmarking Benchmarking TMVA DNN Integration of a Deep Autoencoder
por: Huwiler, Marc
Publicado: (2017)

Applied deep learning with Python: use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions
por: Galea, Alex, et al.
Publicado: (2018)

Deep reinforcement learning hands-on: apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
por: Lapan, Maxim
Publicado: (2018)

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

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

Applied reinforcement learning with Python: with OpenAI Gym, TensorFlow, and Keras
por: Beysolow, Taweh
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)

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

Deep learning for the life sciences: applying deep learning to genomics, microscopy, drug discovery, and more
por: Ramsundar, Bharath, et al.
Publicado: (2019)

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)

Hands-on transfer learning with Python: implement advanced deep learning and neural network models using TensorFlow and Keras
por: Sarkar, Dipanjan, et al.
Publicado: (2018)

Keras reinforcement learning projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents
por: Ciaburro, Giuseppe
Publicado: (2018)

Deep learning with applications using Python: chatbots and face, object, and speech recognition with TensorFlow and Keras
por: Manaswi, Navin Kumar, et al.
Publicado: (2018)

Deep reinforcement learning for wireless networks
por: Yu, F Richard, et al.
Publicado: (2019)

Reinforcement learning: with open AI, TensorFlow and Keras using Python
por: Nandy, Abhishek, et al.
Publicado: (2017)

Reinforcement learning: with Open AI, TensorFlow and Keras using Python
por: Nandy, Abhishek, et al.
Publicado: (2018)

Mastering TensorFlow 1.x: advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
por: Fandango, Armando
Publicado: (2018)

Intelligent projects using Python: 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras
por: Pattanayak, Santanu
Publicado: (2019)

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

Deep learning for computer vision: expert techniques to train advanced neural networks using TensorFlow and Keras
por: Shanmugamani, Rajalingappaa
Publicado: (2018)

Deep autoencoder based domain adaptation for transfer learning
por: Dev, Krishna, et al.
Publicado: (2022)

An autoencoder-based deep learning method for genotype imputation
por: Song, Meng, et al.
Publicado: (2022)

On Scalable Deep Learning and Parallelizing Gradient Descent
por: Hermans, Joeri
Publicado: (2017)

The Deep Learning with Keras Workshop
por: Moocarme, Matthew
Publicado: (2020)

An Introduction to Deep Learning with Keras
por: Paganini, Michela
Publicado: (2016)

Hands-on deep learning for images with TensorFlow: build intelligent computer vision applications using TensorFlow and Keras
por: Ballard, Will
Publicado: (2018)

TensorFlow for deep learning: from linear regression to reinforcement learning
por: Ramsundar, Bharath, et al.
Publicado: (2018)

An Autoencoder-Based Deep Learning Classifier for Efficient Diagnosis of Autism
por: Sewani, Harshini, et al.
Publicado: (2020)

AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders
por: Sajadi, Seyedeh Zahra, et al.
Publicado: (2021)

Deep learning
por: Goodfellow, Ian, et al.
Publicado: (2016)

SASDL and RBATQ: Sparse Autoencoder With Swarm Based Deep Learning and Reinforcement Based Q-Learning for EEG Classification
Publicado: (2022)

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

Hands-on reinforcement learning with Python: master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
por: Ravichandiran, Sudharsan
Publicado: (2018)

Outlier detection using autoencoders
por: Lyudchik, Olga
Publicado: (2016)

Cannot write session to /tmp/vufind_sessions/sess_bj5a2c95ofv469akfcslr99vq5