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Generative Adversarial Networks for Image-to-Image Translation

Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics;

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GANs in Action

images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a;

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Reinforcement Learning for Finance

generative adversarial networks with examples using the TensorFlow Python library. It also serves as a quick hands-on guide to TensorFlow programming;

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Handbook of Decision Support Systems for Neurological Disorders

recent computational approaches, different types of neurological disorders, deep convolution neural networks, generative adversarial networks;

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Python Deep Learning

Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you'll gain an;

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Generative Adversarial Networks Cookbook

generative models with real-world data sets, including 2D and 3D data Book DescriptionDeveloping Generative Adversarial Networks (GANs) is a complex;

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Applied Deep Learning with TensorFlow 2

, metric analysis, and hyper-parameter tuning. In addition, you will learn the fundamentals ideas behind autoencoders and generative adversarial;

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Applied Deep Learning with TensorFlow 2

analysis, and hyper-parameter tuning. In addition, you will learn the fundamentals ideas behind autoencoders and generative adversarial networks;

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Machine Learning for Computer Scientists and Data Analysts

, through complex neural networks, including generative adversarial neural networks and graph convolution networks. Most importantly, this book;

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Generative Deep Learning Teaching Machines to Paint, Write, Compose and Play

most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder;

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Generative Adversarial Networks for Image Generation

Generative adversarial networks (GANs) were introduced by Ian Goodfellow and his co-authors including Yoshua Bengio in 2014, and were to;

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Practical TensorFlow.js

(RNN), and generative adversarial network (GAN). Through hands-on examples, apply these networks in use cases related to image classification;

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Practical TensorFlow.js

(RNN), and generative adversarial network (GAN). Through hands-on examples, apply these networks in use cases related to image classification;

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Biological and Computer Vision

cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among;

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Biological and Computer Vision

cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among;

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Strengthening Deep Neural Networks Making AI Less Susceptible to Adversarial Trickery

this adversarial input, and methods for increasing AI robustness to these attacks. If you're a data scientist developing DNN algorithms, a;

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Proceedings of International Conference on Scientific and Natural Computing

, generative adversarial networks and auto-encoders, bio-inspired systems, data mining, data visualization, intelligent agents, engineering design;

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Introduction to Machine Learning with Applications in Information Security

Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief;

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Deep Learning with R Cookbook

years with developments such as generative adversarial networks (GANs), variational autoencoders (VAEs), and deep reinforcement learning. This;

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Advanced Deep Learning with Keras

learning, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Deep Reinforcement Learning (DRL) are creating;

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Practical Convolutional Neural Networks

object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models;

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Machine Learning

, recurrent neural networks, attention mechanisms, adversarial examples and training, capsule networks and generative architectures, such as;

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Generative AI with Python and TensorFlow 2

Fun and exciting projects to learn what artificial minds can create Key Features Code examples;...

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Machine Learning for Future Fiber-Optic Communication Systems

), and generative adversarial networks (GANs) Individual chapters focus on ML applications in key areas of optical;

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Medical Image Computing and Computer Assisted Intervention MICCAI 2020

learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase;

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Medical Image Computing and Computer Assisted Intervention MICCAI 2020

; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and;

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Medical Image Computing and Computer Assisted Intervention MICCAI 2020

; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and;

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