Gans In Action
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Gans In Action
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Author : Vladimir Bok
language : en
Publisher: Simon and Schuster
Release Date : 2019-09-09
Gans In Action written by Vladimir Bok and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-09 with Computers categories.
Deep learning systems have gotten really great at identifying patterns in text, images, and video. But applications that create realistic images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a promising solution to these challenges by pairing two competing neural networks' one that generates content and the other that rejects samples that are of poor quality. GANs in Action: Deep learning with Generative Adversarial Networks teaches you how to build and train your own generative adversarial networks. First, you'll get an introduction to generative modelling and how GANs work, along with an overview of their potential uses. Then, you'll start building your own simple adversarial system, as you explore the foundation of GAN architecture: the generator and discriminator networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Gans In Action
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Author : Jakub Langr
language : en
Publisher: Manning
Release Date : 2019-10-07
Gans In Action written by Jakub Langr and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-07 with Computers categories.
Deep learning systems have gotten really great at identifying patterns in text, images, and video. But applications that create realistic images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a promising solution to these challenges by pairing two competing neural networks' one that generates content and the other that rejects samples that are of poor quality. GANs in Action: Deep learning with Generative Adversarial Networks teaches you how to build and train your own generative adversarial networks. First, you'll get an introduction to generative modelling and how GANs work, along with an overview of their potential uses. Then, you'll start building your own simple adversarial system, as you explore the foundation of GAN architecture: the generator and discriminator networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Gans In Action
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Author : Jakub Langr
language : en
Publisher:
Release Date : 2021
Gans In Action written by Jakub Langr and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Machine learning categories.
Generative Adversarial Networks, GANs, are an incredible AI technology capable of creating images, sound, and videos that are indistinguishable from the "real thing". By pitting two neural networks against each other, one to generate fakes and one to spot them, GANs rapidly learn to produce photo-realistic faces and other media objects. With the potential to produce stunningly realistic animations or shocking deepfakes, GANs are a huge step forward in deep learning systems. "GANs in action" teaches you to build and train your own Generative Adversarial Networks. You'll start by creating simple generator and discriminator networks that are the foundation of GAN architecture. Then, following numerous hands-on examples, you'll train GANs to generate high-resolution images, image-to-image translation, and targeted data generation. Along the way, you'll find pro tips for making your system smart, effective, and fast.
Generative Adversarial Networks Cookbook
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Author : Josh Kalin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-31
Generative Adversarial Networks Cookbook written by Josh Kalin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-31 with Computers categories.
Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key FeaturesUnderstand the common architecture of different types of GANsTrain, optimize, and deploy GAN applications using TensorFlow and KerasBuild generative models with real-world data sets, including 2D and 3D dataBook Description Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand. This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use. By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away. What you will learnStructure a GAN architecture in pseudocodeUnderstand the common architecture for each of the GAN models you will buildImplement different GAN architectures in TensorFlow and KerasUse different datasets to enable neural network functionality in GAN modelsCombine different GAN models and learn how to fine-tune themProduce a model that can take 2D images and produce 3D modelsDevelop a GAN to do style transfer with Pix2PixWho this book is for This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.
Global Action Networks
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Author : Steve Waddell
language : en
Publisher: Springer
Release Date : 2010-12-08
Global Action Networks written by Steve Waddell and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-08 with Business & Economics categories.
The world's governments are overwhelmed with climate change, war and unrest, the global financial crisis and poverty but there is a promising invention in Global Action Networks (GANs). GANs mobilize resources, bridge divides and promote the long-term deep change and innovation work that is needed to address the global challenges.
Generative Deep Learning
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Author : David Foster
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-06-28
Generative Deep Learning written by David Foster and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-28 with Computers categories.
Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN
Electromyography For Experimentalists
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Author : Gerald E. Loeb
language : en
Publisher: University of Chicago Press
Release Date : 1986
Electromyography For Experimentalists written by Gerald E. Loeb and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Medical categories.
The technique of electromyography, used to study the electrical currents generated by muscle action, has become invaluable to researchers in the biological, medical, and behavioral sciences. With it, the scientist can study the role of muscles in producing and controlling limb movement, eating, breathing, posture, vocalizations, and the manipulation of objects. However, many electromyographic techniques were developed in the clinical study of humans and are inappropriate for use in research on other organisms--tadpoles, for example. This book, a complete and very practical hands-on guide to the theoretical and experimental requirements of electromyography, takes into account the needs of researchers across the sciences.
Elixir In Action
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Author : Sasa Juric
language : en
Publisher: Simon and Schuster
Release Date : 2019-01-03
Elixir In Action written by Sasa Juric and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-03 with Computers categories.
Summary Revised and updated for Elixir 1.7, Elixir in Action, Second Edition teaches you how to apply Elixir to practical problems associated with scalability, fault tolerance, and high availability. Along the way, you'll develop an appreciation for, and considerable skill in, a functional and concurrent style of programming. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology When you're building mission-critical software, fault tolerance matters. The Elixir programming language delivers fast, reliable applications, whether you're building a large-scale distributed system, a set of backend services, or a simple web app. And Elixir's elegant syntax and functional programming mindset make your software easy to write, read, and maintain. About the Book Elixir in Action, Second Edition teaches you how to build production-quality distributed applications using the Elixir programming language. Author Saša Jurić introduces this powerful language using examples that highlight the benefits of Elixir's functional and concurrent programming. You'll discover how the OTP framework can radically reduce tedious low-level coding tasks. You'll also explore practical approaches to concurrency as you learn to distribute a production system over multiple machines. What's inside Updated for Elixir 1.7 Functional and concurrent programming Introduction to distributed system design Creating deployable releases About the Reader You'll need intermediate skills with client/server applications and a language like Java, C#, or Ruby. No previous experience with Elixir required. About the Author Saša Jurić is a developer with extensive experience using Elixir and Erlang in complex server-side systems. Table of Contents First steps Building blocks Control flow Data abstractions Concurrency primitives Generic server processes Building a concurrent system Fault-tolerance basics Isolating error effects Beyond GenServer Working with components Building a distributed system Running the system
Deep Learning
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Author : Ian Goodfellow
language : en
Publisher: MIT Press
Release Date : 2016-11-10
Deep Learning written by Ian Goodfellow and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-10 with Computers categories.
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.