Deep Learning Applications Volume 3

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Deep Learning Applications, Volume 3

Author : M. Arif Wani,Bhiksha Raj,Feng Luo,Dejing Dou
Publisher : Springer Nature
Page : 328 pages
File Size : 44,8 Mb
Release : 2021-11-12
Category : Technology & Engineering
ISBN : 9789811633577

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Deep Learning Applications, Volume 3 by M. Arif Wani,Bhiksha Raj,Feng Luo,Dejing Dou Pdf

This book presents a compilation of extended version of selected papers from the 19th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2020) and focuses on deep learning networks in applications such as pneumonia detection in chest X-ray images, object detection and classification, RGB and depth image fusion, NLP tasks, dimensionality estimation, time series forecasting, building electric power grid for controllable energy resources, guiding charities in maximizing donations, and robotic control in industrial environments. Novel ways of using convolutional neural networks, recurrent neural network, autoencoder, deep evidential active learning, deep rapid class augmentation techniques, BERT models, multi-task learning networks, model compression and acceleration techniques, and conditional Feature Augmented and Transformed GAN (cFAT-GAN) for the above applications are covered in this book. Readers will find insights to help them realize novel ways of using deep learning architectures and algorithms in real-world applications and contexts, making the book an essential reference guide for academic researchers, professionals, software engineers in the industry, and innovative product developers.

Deep Learning

Author : Ian Goodfellow,Yoshua Bengio,Aaron Courville
Publisher : MIT Press
Page : 801 pages
File Size : 55,7 Mb
Release : 2016-11-10
Category : Computers
ISBN : 9780262337373

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Deep Learning by Ian Goodfellow,Yoshua Bengio,Aaron Courville Pdf

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.

Handbook of Deep Learning Applications

Author : Valentina Emilia Balas,Sanjiban Sekhar Roy,Dharmendra Sharma,Pijush Samui
Publisher : Springer
Page : 383 pages
File Size : 43,7 Mb
Release : 2019-02-25
Category : Technology & Engineering
ISBN : 9783030114794

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Handbook of Deep Learning Applications by Valentina Emilia Balas,Sanjiban Sekhar Roy,Dharmendra Sharma,Pijush Samui Pdf

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.

Artificial Intelligence for Humans

Author : Jeff Heaton
Publisher : Createspace Independent Publishing Platform
Page : 0 pages
File Size : 46,5 Mb
Release : 2015
Category : Algorithms
ISBN : 1505714346

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Artificial Intelligence for Humans by Jeff Heaton Pdf

« Artifical Intelligence for Humans is a book series meant to teach AI to those readers who lack an extensive mathematical background. The reader only needs knowledge of basic college algebra and computer programming. Additional topics are thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, and Python. Other languages are planned. »--

Machine Learning and Its Applications

Author : Georgios Paliouras,Vangelis Karkaletsis,Constantine D. Spyropoulos
Publisher : Springer
Page : 324 pages
File Size : 55,5 Mb
Release : 2003-06-29
Category : Computers
ISBN : 9783540446736

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Machine Learning and Its Applications by Georgios Paliouras,Vangelis Karkaletsis,Constantine D. Spyropoulos Pdf

In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers. This book presents the capabilities of machine learning methods and ideas on how these methods could be used to solve real-world problems. The first ten chapters assess the current state of the art of machine learning, from symbolic concept learning and conceptual clustering to case-based reasoning, neural networks, and genetic algorithms. The second part introduces the reader to innovative applications of ML techniques in fields such as data mining, knowledge discovery, human language technology, user modeling, data analysis, discovery science, agent technology, finance, etc.

Deep Learning: Fundamentals, Theory and Applications

Author : Kaizhu Huang,Amir Hussain,Qiu-Feng Wang,Rui Zhang
Publisher : Springer
Page : 163 pages
File Size : 54,7 Mb
Release : 2019-02-15
Category : Medical
ISBN : 9783030060732

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Deep Learning: Fundamentals, Theory and Applications by Kaizhu Huang,Amir Hussain,Qiu-Feng Wang,Rui Zhang Pdf

The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field. This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in studying or exploring the potential of exploiting deep learning algorithms. It will also be of special interest to researchers in the area of AI, pattern recognition, machine learning and related areas, alongside engineers interested in applying deep learning models in existing or new practical applications.

Deep Learning: Algorithms and Applications

Author : Witold Pedrycz,Shyi-Ming Chen
Publisher : Springer Nature
Page : 360 pages
File Size : 50,5 Mb
Release : 2019-10-23
Category : Technology & Engineering
ISBN : 9783030317607

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Deep Learning: Algorithms and Applications by Witold Pedrycz,Shyi-Ming Chen Pdf

This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm’s algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.

Building Machine Learning Powered Applications

Author : Emmanuel Ameisen
Publisher : "O'Reilly Media, Inc."
Page : 267 pages
File Size : 47,5 Mb
Release : 2020-01-21
Category : Computers
ISBN : 9781492045069

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Building Machine Learning Powered Applications by Emmanuel Ameisen Pdf

Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers—including experienced practitioners and novices alike—will learn the tools, best practices, and challenges involved in building a real-world ML application step by step. Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies. This book will help you: Define your product goal and set up a machine learning problem Build your first end-to-end pipeline quickly and acquire an initial dataset Train and evaluate your ML models and address performance bottlenecks Deploy and monitor your models in a production environment

Deep Learning Applications, Volume 2

Author : M. Arif Wani,Taghi Khoshgoftaar,Vasile Palade
Publisher : Springer
Page : 300 pages
File Size : 42,9 Mb
Release : 2020-12-14
Category : Technology & Engineering
ISBN : 9811567581

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Deep Learning Applications, Volume 2 by M. Arif Wani,Taghi Khoshgoftaar,Vasile Palade Pdf

This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

Deep Learning in Healthcare

Author : Yen-Wei Chen,Lakhmi C. Jain
Publisher : Springer Nature
Page : 225 pages
File Size : 48,5 Mb
Release : 2019-11-18
Category : Technology & Engineering
ISBN : 9783030326067

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Deep Learning in Healthcare by Yen-Wei Chen,Lakhmi C. Jain Pdf

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.

Deep Learning Applications, Volume 4

Author : M. Arif Wani,Vasile Palade
Publisher : Springer Nature
Page : 394 pages
File Size : 41,5 Mb
Release : 2022-11-25
Category : Technology & Engineering
ISBN : 9789811961533

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Deep Learning Applications, Volume 4 by M. Arif Wani,Vasile Palade Pdf

This book presents a compilation of extended versions of selected papers from 20th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2021). It focuses on deep learning networks and their applications in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers. The book is fourth in the series published since 2017.

Deep Learning Applications

Author : Pier Luigi Mazzeo,Paolo Spagnolo
Publisher : BoD – Books on Demand
Page : 216 pages
File Size : 54,9 Mb
Release : 2021-07-14
Category : Computers
ISBN : 9781839623745

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Deep Learning Applications by Pier Luigi Mazzeo,Paolo Spagnolo Pdf

Deep learning is a branch of machine learning similar to artificial intelligence. The applications of deep learning vary from medical imaging to industrial quality checking, sports, and precision agriculture. This book is divided into two sections. The first section covers deep learning architectures and the second section describes the state of the art of applications based on deep learning.

Deep Learning Applications, Volume 2

Author : M. Arif Wani,Taghi M. Khoshgoftaar,Vasile Palade
Publisher : Unknown
Page : 0 pages
File Size : 52,9 Mb
Release : 2021
Category : Electronic
ISBN : 9811567603

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Deep Learning Applications, Volume 2 by M. Arif Wani,Taghi M. Khoshgoftaar,Vasile Palade Pdf

This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

Machine Learning Paradigms

Author : Maria Virvou,Efthimios Alepis,George A. Tsihrintzis,Lakhmi C. Jain
Publisher : Springer
Page : 223 pages
File Size : 44,8 Mb
Release : 2019-03-16
Category : Technology & Engineering
ISBN : 9783030137434

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Machine Learning Paradigms by Maria Virvou,Efthimios Alepis,George A. Tsihrintzis,Lakhmi C. Jain Pdf

This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators’ and learners’ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including: • Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation; • Using learning analytics to predict student performance; • Using learning analytics to create learning materials and educational courses; and • Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.

Deep Learning Applications, Volume 2

Author : M. Arif Wani,Taghi M. Khoshgoftaar,Vasile Palade
Publisher : Springer Nature
Page : 307 pages
File Size : 52,9 Mb
Release : 2020-09-24
Category : Technology & Engineering
ISBN : 9789811567599

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Deep Learning Applications, Volume 2 by M. Arif Wani,Taghi M. Khoshgoftaar,Vasile Palade Pdf

This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.