Deep Belief Nets In C And Cuda C Volume 2
DOWNLOAD
Download Deep Belief Nets In C And Cuda C Volume 2 PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Deep Belief Nets In C And Cuda C Volume 2 book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Deep Belief Nets In C And Cuda C Volume 2
DOWNLOAD
Author : Timothy Masters
language : en
Publisher: Apress
Release Date : 2018-05-29
Deep Belief Nets In C And Cuda C Volume 2 written by Timothy Masters and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-29 with Computers categories.
Discover the essential building blocks of a common and powerful form of deep belief net: the autoencoder. You’ll take this topic beyond current usage by extending it to the complex domain for signal and image processing applications. Deep Belief Nets in C++ and CUDA C: Volume 2 also covers several algorithms for preprocessing time series and image data. These algorithms focus on the creation of complex-domain predictors that are suitable for input to a complex-domain autoencoder. Finally, you’ll learn a method for embedding class information in the input layer of a restricted Boltzmann machine. This facilitates generative display of samples from individual classes rather than the entire data distribution. The ability to see the features that the model has learned for each class separately can be invaluable. At each step this book provides you with intuitive motivation, a summary of the most important equations relevant to the topic, and highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. What You'll Learn Code for deep learning, neural networks, and AI using C++ and CUDA C Carry out signal preprocessing using simple transformations, Fourier transforms, Morlet wavelets, and more Use the Fourier Transform for image preprocessing Implement autoencoding via activation in the complex domain Work with algorithms for CUDA gradient computation Use the DEEP operating manual Who This Book Is For Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.
Deep Belief Nets In C And Cuda C Volume 3
DOWNLOAD
Author : Timothy Masters
language : en
Publisher: Apress
Release Date : 2018-07-04
Deep Belief Nets In C And Cuda C Volume 3 written by Timothy Masters and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Computers categories.
Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a ‘thought process’ that is capable of learning abstract concepts built from simpler primitives. These models are especially useful for image processing applications. At each step Deep Belief Nets in C++ and CUDA C: Volume 3 presents intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. Source code for all routines presented in the book, and the executable CONVNET program which implements these algorithms, are available for free download. What You Will Learn Discover convolutional nets and how to use them Build deep feedforward nets using locally connected layers, pooling layers, and softmax outputs Master the various programming algorithms required Carry out multi-threaded gradient computations and memory allocations for this threading Work with CUDA code implementations of all core computations, including layer activations and gradient calculations Make use of the CONVNET program and manual to explore convolutional nets and case studies Who This Book Is For Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.
Deep Belief Nets In C And Cuda C Volume 1
DOWNLOAD
Author : Timothy Masters
language : en
Publisher: Apress
Release Date : 2018-04-23
Deep Belief Nets In C And Cuda C Volume 1 written by Timothy Masters and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-23 with Computers categories.
Discover the essential building blocks of the most common forms of deep belief networks. At each step this book provides intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. The first of three in a series on C++ and CUDA C deep learning and belief nets, Deep Belief Nets in C++ and CUDA C: Volume 1 shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a thought process that is capable of learning abstract concepts built from simpler primitives. As such, you’ll see that a typical deep belief net can learn to recognize complex patterns by optimizing millions of parameters, yet this model can still be resistant to overfitting. All theroutines and algorithms presented in the book are available in the code download, which also contains some libraries of related routines. What You Will Learn Employ deep learning using C++ and CUDA C Work with supervised feedforward networks Implement restricted Boltzmann machines Use generative samplings Discover why these are important Who This Book Is For Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.
Handbook Of Research On Big Data Storage And Visualization Techniques
DOWNLOAD
Author : Segall, Richard S.
language : en
Publisher: IGI Global
Release Date : 2018-01-05
Handbook Of Research On Big Data Storage And Visualization Techniques written by Segall, Richard S. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-05 with Computers categories.
The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.
Deep Belief Nets In C And Cuda C
DOWNLOAD
Author : Timothy Masters
language : en
Publisher: CreateSpace
Release Date : 2015-02-11
Deep Belief Nets In C And Cuda C written by Timothy Masters and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-11 with Computers categories.
Deep belief nets are one of the most exciting recent developments in artificial intelligence. The structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a 'thought process' that is capable of learning abstract concepts built from simpler primitives. A typical deep belief net can learn to recognize complex patterns by optimizing millions of parameters, yet this model can still be resistant to overfitting. This book presents the essential building blocks of the most common forms of deep belief nets. At each step the text provides intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. Source code for all routines presented in the book, and the DEEP program which implements these algorithms, are available for free download from the author's website.
Pro Hadoop Data Analytics
DOWNLOAD
Author : Kerry Koitzsch
language : en
Publisher: Apress
Release Date : 2016-12-29
Pro Hadoop Data Analytics written by Kerry Koitzsch and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-29 with Computers categories.
Learn advanced analytical techniques and leverage existing tool kits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems that go beyond the basics of classification, clustering, and recommendation. Pro Hadoop Data Analytics emphasizes best practices to ensure coherent, efficient development. A complete example system will be developed using standard third-party components that consist of the tool kits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system. The book also highlights the importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. You'll discover the importance of mix-and-match or hybrid systems, using different analytical components in one application. This hybrid approach will be prominent in the examples. What You'll Learn Build big data analytic systems with the Hadoop ecosystem Use libraries, tool kits, and algorithms to make development easier and more effective Apply metrics to measure performance and efficiency of components and systems Connect to standard relational databases, noSQL data sources, and more Follow case studies with example components to create your own systems Who This Book Is For Software engineers, architects, and data scientists with an interest in the design and implementation of big data analytical systems using Hadoop, the Hadoop ecosystem, and other associated technologies.
Advances In Information And Communication
DOWNLOAD
Author : Kohei Arai
language : en
Publisher: Springer
Release Date : 2019-02-01
Advances In Information And Communication written by Kohei Arai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-01 with Technology & Engineering categories.
This book presents a remarkable collection of chapters that cover a wide range of topics in the areas of information and communication technologies and their real-world applications. It gathers the Proceedings of the Future of Information and Communication Conference 2019 (FICC 2019), held in San Francisco, USA from March 14 to 15, 2019. The conference attracted a total of 462 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. Following a double-blind peer review process, 160 submissions (including 15 poster papers) were ultimately selected for inclusion in these proceedings. The papers highlight relevant trends in, and the latest research on: Communication, Data Science, Ambient Intelligence, Networking, Computing, Security, and the Internet of Things. Further, they address all aspects of Information Science and communication technologies, from classical to intelligent, and both the theory and applications of the latest technologies and methodologies. Gathering chapters that discuss state-of-the-art intelligent methods and techniques for solving real-world problems, along with future research directions, the book represents both an interesting read and a valuable asset.
Machine Learning For Adaptive Many Core Machines A Practical Approach
DOWNLOAD
Author : Noel Lopes
language : en
Publisher: Springer
Release Date : 2014-06-28
Machine Learning For Adaptive Many Core Machines A Practical Approach written by Noel Lopes and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Technology & Engineering categories.
The overwhelming data produced everyday and the increasing performance and cost requirements of applications are transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data. This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind. It presents a series of new techniques to enhance, scale and distribute data in a Big Learning framework. It is not intended to be a comprehensive survey of the state of the art of the whole field of machine learning for Big Data. Its purpose is less ambitious and more practical: to explain and illustrate existing and novel GPU-based ML algorithms, not viewed as a universal solution for the Big Data challenges but rather as part of the answer, which may require the use of different strategies coupled together.
Machine Learning Based Modelling In Atomic Layer Deposition Processes
DOWNLOAD
Author : Oluwatobi Adeleke
language : en
Publisher: CRC Press
Release Date : 2023-12-15
Machine Learning Based Modelling In Atomic Layer Deposition Processes written by Oluwatobi Adeleke and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-15 with Technology & Engineering categories.
While thin film technology has benefited greatly from artificial intelligence (AI) and machine learning (ML) techniques, there is still much to be learned from a full-scale exploration of these technologies in atomic layer deposition (ALD). This book provides in-depth information regarding the application of ML-based modeling techniques in thin film technology as a standalone approach and integrated with the classical simulation and modeling methods. It is the first of its kind to present detailed information regarding approaches in ML-based modeling, optimization, and prediction of the behaviors and characteristics of ALD for improved process quality control and discovery of new materials. As such, this book fills significant knowledge gaps in the existing resources as it provides extensive information on ML and its applications in film thin technology. Offers an in-depth overview of the fundamentals of thin film technology, state-of-the-art computational simulation approaches in ALD, ML techniques, algorithms, applications, and challenges. Establishes the need for and significance of ML applications in ALD while introducing integration approaches for ML techniques with computation simulation approaches. Explores the application of key techniques in ML, such as predictive analysis, classification techniques, feature engineering, image processing capability, and microstructural analysis of deep learning algorithms and generative model benefits in ALD. Helps readers gain a holistic understanding of the exciting applications of ML-based solutions to ALD problems and apply them to real-world issues. Aimed at materials scientists and engineers, this book fills significant knowledge gaps in existing resources as it provides extensive information on ML and its applications in film thin technology. It also opens space for future intensive research and intriguing opportunities for ML-enhanced ALD processes, which scale from academic to industrial applications.
Artificial Neural Networks Icann 2010
DOWNLOAD
Author : Konstantinos Diamantaras
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-03
Artificial Neural Networks Icann 2010 written by Konstantinos Diamantaras and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-03 with Computers categories.
This three volume set LNCS 6352, LNCS 6353, and LNCS 6354 constitutes the refereed proceedings of the 20th International Conference on Artificial Neural Networks, ICANN 2010, held in Thessaloniki, Greece, in September 20010. The 102 revised full papers, 68 short papers and 29 posters presented were carefully reviewed and selected from 241 submissions. The third volume is divided in topical sections on classification – pattern recognition, learning algorithms and systems, computational intelligence, IEM3 workshop, CVA workshop, and SOINN workshop.