Innovations In Machine And Deep Learning

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Innovations in Machine and Deep Learning

Gilberto Rivera,Alejandro Rosete,Bernabé Dorronsoro,Nelson Rangel-Valdez
Innovations in Machine and Deep Learning Book PDF

Author : Gilberto Rivera,Alejandro Rosete,Bernabé Dorronsoro,Nelson Rangel-Valdez
Publisher : Springer Nature
Page : 506 pages
File Size : 43,7 Mb
Release : 2023-11-04
Category : Computers
ISBN : 9783031406881

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Innovations in Machine and Deep Learning by Gilberto Rivera,Alejandro Rosete,Bernabé Dorronsoro,Nelson Rangel-Valdez Pdf

In recent years, significant progress has been made in achieving artificial intelligence (AI) with an impact on students, managers, scientists, health personnel, technical roles, investors, teachers, and leaders. This book presents numerous successful applications of AI in various contexts. The innovative implications covered fall under the general field of machine learning (ML), including deep learning, decision-making, forecasting, pattern recognition, information retrieval, and interpretable AI. Decision-makers and entrepreneurs will find numerous successful applications in health care, sustainability, risk management, human activity recognition, logistics, and Industry 4.0. This book is an essential resource for anyone interested in challenges, opportunities, and the latest developments and real-world applications of ML. Whether you are a student, researcher, practitioner, or simply curious about AI, this book provides valuable insights and inspiration for your work and learning.

Advances in Machine Learning/Deep Learning-based Technologies

George A. Tsihrintzis,Maria Virvou,Lakhmi C. Jain
Advances in Machine Learning Deep Learning based Technologies Book PDF

Author : George A. Tsihrintzis,Maria Virvou,Lakhmi C. Jain
Publisher : Springer Nature
Page : 237 pages
File Size : 44,7 Mb
Release : 2021-08-05
Category : Technology & Engineering
ISBN : 9783030767945

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Advances in Machine Learning/Deep Learning-based Technologies by George A. Tsihrintzis,Maria Virvou,Lakhmi C. Jain Pdf

As the 4th Industrial Revolution is restructuring human societal organization into, so-called, “Society 5.0”, the field of Machine Learning (and its sub-field of Deep Learning) and related technologies is growing continuously and rapidly, developing in both itself and towards applications in many other disciplines. Researchers worldwide aim at incorporating cognitive abilities into machines, such as learning and problem solving. When machines and software systems have been enhanced with Machine Learning/Deep Learning components, they become better and more efficient at performing specific tasks. Consequently, Machine Learning/Deep Learning stands out as a research discipline due to its worldwide pace of growth in both theoretical advances and areas of application, while achieving very high rates of success and promising major impact in science, technology and society. The book at hand aims at exposing its readers to some of the most significant Advances in Machine Learning/Deep Learning-based Technologies. The book consists of an editorial note and an additional ten (10) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into five parts, namely (i) Machine Learning/Deep Learning in Socializing and Entertainment, (ii) Machine Learning/Deep Learning in Education, (iii) Machine Learning/Deep Learning in Security, (iv) Machine Learning/Deep Learning in Time Series Forecasting, and (v) Machine Learning in Video Coding and Information Extraction. This research book is directed towards professors, researchers, scientists, engineers and students in Machine Learning/Deep Learning-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent Machine Learning/Deep Learning-based technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe further into the application areas of interest to them.

The Development of Deep Learning Technologies

China Info & Comm Tech Grp Corp
The Development of Deep Learning Technologies Book PDF

Author : China Info & Comm Tech Grp Corp
Publisher : Springer Nature
Page : 68 pages
File Size : 46,7 Mb
Release : 2020-07-13
Category : Computers
ISBN : 9789811545849

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The Development of Deep Learning Technologies by China Info & Comm Tech Grp Corp Pdf

This book is a part of the Blue Book series “Research on the Development of Electronic Information Engineering Technology in China,” which explores the cutting edge of deep learning studies. A subfield of machine learning, deep learning differs from conventional machine learning methods in its ability to learn multiple levels of representation and abstraction by using several layers of nonlinear modules for feature extraction and transformation. The extensive use and huge success of deep learning in speech, CV, and NLP have led to significant advances toward the full materialization of AI. Focusing on the development of deep learning technologies, this book also discusses global trends, the status of deep learning development in China and the future of deep learning.

Deep Neural Network Applications

Hasmik Osipyan,Bosede Iyiade Edwards,Adrian David Cheok
Deep Neural Network Applications Book PDF

Author : Hasmik Osipyan,Bosede Iyiade Edwards,Adrian David Cheok
Publisher : CRC Press
Page : 158 pages
File Size : 43,7 Mb
Release : 2022-04-28
Category : Computers
ISBN : 9780429556203

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Deep Neural Network Applications by Hasmik Osipyan,Bosede Iyiade Edwards,Adrian David Cheok Pdf

The world is on the verge of fully ushering in the fourth industrial revolution, of which artificial intelligence (AI) is the most important new general-purpose technology. Like the steam engine that led to the widespread commercial use of driving machineries in the industries during the first industrial revolution; the internal combustion engine that gave rise to cars, trucks, and airplanes; electricity that caused the second industrial revolution through the discovery of direct and alternating current; and the Internet, which led to the emergence of the information age, AI is a transformational technology. It will cause a paradigm shift in the way’s problems are solved in every aspect of our lives, and, from it, innovative technologies will emerge. AI is the theory and development of machines that can imitate human intelligence in tasks such as visual perception, speech recognition, decision-making, and human language translation. This book provides a complete overview on the deep learning applications and deep neural network architectures. It also gives an overview on most advanced future-looking fundamental research in deep learning application in artificial intelligence. Research overview includes reasoning approaches, problem solving, knowledge representation, planning, learning, natural language processing, perception, motion and manipulation, social intelligence and creativity. It will allow the reader to gain a deep and broad knowledge of the latest engineering technologies of AI and Deep Learning and is an excellent resource for academic research and industry applications.

Deep Learning Innovations and Their Convergence With Big Data

Karthik, S.,Paul, Anand,Karthikeyan, N.
Deep Learning Innovations and Their Convergence With Big Data Book PDF

Author : Karthik, S.,Paul, Anand,Karthikeyan, N.
Publisher : IGI Global
Page : 265 pages
File Size : 51,9 Mb
Release : 2017-07-13
Category : Computers
ISBN : 9781522530169

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Deep Learning Innovations and Their Convergence With Big Data by Karthik, S.,Paul, Anand,Karthikeyan, N. Pdf

The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics. Deep Learning Innovations and Their Convergence With Big Data is a pivotal reference for the latest scholarly research on upcoming trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. Featuring extensive coverage on a broad range of topics and perspectives such as deep neural network, domain adaptation modeling, and threat detection, this book is ideally designed for researchers, professionals, and students seeking current research on the latest trends in the field of deep learning techniques in big data analytics.

Advances in Machine Learning/Deep Learning-based Technologies

George A. Tsihrintzis,Maria Virvou,Lakhmi C. Jain
Advances in Machine Learning Deep Learning based Technologies Book PDF

Author : George A. Tsihrintzis,Maria Virvou,Lakhmi C. Jain
Publisher : Unknown
Page : 0 pages
File Size : 42,9 Mb
Release : 2022
Category : Electronic
ISBN : 3030767957

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Advances in Machine Learning/Deep Learning-based Technologies by George A. Tsihrintzis,Maria Virvou,Lakhmi C. Jain Pdf

As the 4th Industrial Revolution is restructuring human societal organization into, so-called, "Society 5.0", the field of Machine Learning (and its sub-field of Deep Learning) and related technologies is growing continuously and rapidly, developing in both itself and towards applications in many other disciplines. Researchers worldwide aim at incorporating cognitive abilities into machines, such as learning and problem solving. When machines and software systems have been enhanced with Machine Learning/Deep Learning components, they become better and more efficient at performing specific tasks. Consequently, Machine Learning/Deep Learning stands out as a research discipline due to its worldwide pace of growth in both theoretical advances and areas of application, while achieving very high rates of success and promising major impact in science, technology and society. The book at hand aims at exposing its readers to some of the most significant Advances in Machine Learning/Deep Learning-based Technologies. The book consists of an editorial note and an additional ten (10) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into five parts, namely (i) Machine Learning/Deep Learning in Socializing and Entertainment, (ii) Machine Learning/Deep Learning in Education, (iii) Machine Learning/Deep Learning in Security, (iv) Machine Learning/Deep Learning in Time Series Forecasting, and (v) Machine Learning in Video Coding and Information Extraction. This research book is directed towards professors, researchers, scientists, engineers and students in Machine Learning/Deep Learning-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent Machine Learning/Deep Learning-based technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe further into the application areas of interest to them.

Advanced Machine Learning Technologies and Applications

Aboul-Ella Hassanien,Kuo-Chi Chang,Tang Mincong
Advanced Machine Learning Technologies and Applications Book PDF

Author : Aboul-Ella Hassanien,Kuo-Chi Chang,Tang Mincong
Publisher : Springer Nature
Page : 1144 pages
File Size : 47,6 Mb
Release : 2021-03-04
Category : Technology & Engineering
ISBN : 9783030697174

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Advanced Machine Learning Technologies and Applications by Aboul-Ella Hassanien,Kuo-Chi Chang,Tang Mincong Pdf

This book presents the refereed proceedings of the 6th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA 2021) held in Cairo, Egypt, during March 22–24, 2021, and organized by the Scientific Research Group of Egypt (SRGE). The papers cover current research Artificial Intelligence Against COVID-19, Internet of Things Healthcare Systems, Deep Learning Technology, Sentiment analysis, Cyber-Physical System, Health Informatics, Data Mining, Power and Control Systems, Business Intelligence, Social media, Control Design, and Smart Systems.

Practical Machine Learning: Innovations in Recommendation

Ted Dunning,Ellen Friedman,Ellen Friedman, M D
Practical Machine Learning Innovations in Recommendation Book PDF

Author : Ted Dunning,Ellen Friedman,Ellen Friedman, M D
Publisher : "O'Reilly Media, Inc."
Page : 55 pages
File Size : 48,8 Mb
Release : 2014-08-18
Category : Computers
ISBN : 9781491915721

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Practical Machine Learning: Innovations in Recommendation by Ted Dunning,Ellen Friedman,Ellen Friedman, M D Pdf

Building a simple but powerful recommendation system is much easier than you think. Approachable for all levels of expertise, this report explains innovations that make machine learning practical for business production settings—and demonstrates how even a small-scale development team can design an effective large-scale recommendation system. Apache Mahout committers Ted Dunning and Ellen Friedman walk you through a design that relies on careful simplification. You’ll learn how to collect the right data, analyze it with an algorithm from the Mahout library, and then easily deploy the recommender using search technology, such as Apache Solr or Elasticsearch. Powerful and effective, this efficient combination does learning offline and delivers rapid response recommendations in real time. Understand the tradeoffs between simple and complex recommenders Collect user data that tracks user actions—rather than their ratings Predict what a user wants based on behavior by others, using Mahoutfor co-occurrence analysis Use search technology to offer recommendations in real time, complete with item metadata Watch the recommender in action with a music service example Improve your recommender with dithering, multimodal recommendation, and other techniques

Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches

Chiranji Lal Chowdhary,Mamoun Alazab,Ankit Chaudhary,Saqib Hakak,Thippa Reddy Gadekallu
Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches Book PDF

Author : Chiranji Lal Chowdhary,Mamoun Alazab,Ankit Chaudhary,Saqib Hakak,Thippa Reddy Gadekallu
Publisher : Computing and Networks
Page : 504 pages
File Size : 42,9 Mb
Release : 2021-11
Category : Computers
ISBN : 1839533234

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Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches by Chiranji Lal Chowdhary,Mamoun Alazab,Ankit Chaudhary,Saqib Hakak,Thippa Reddy Gadekallu Pdf

Written by a team of International experts, this edited book covers state-of-the-art research in the fields of computer vision and recognition systems from fundamental concepts to methodologies and technologies and real-world applications. The book will be useful for industry and academic researchers, scientists and engineers.

Advanced Analytics and Deep Learning Models

Archana Mire,Shaveta Malik,Amit Kumar Tyagi
Advanced Analytics and Deep Learning Models Book PDF

Author : Archana Mire,Shaveta Malik,Amit Kumar Tyagi
Publisher : John Wiley & Sons
Page : 436 pages
File Size : 43,7 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9781119791751

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Advanced Analytics and Deep Learning Models by Archana Mire,Shaveta Malik,Amit Kumar Tyagi Pdf

Advanced Analytics and Deep Learning Models The book provides readers with an in-depth understanding of concepts and technologies related to the importance of analytics and deep learning in many useful real-world applications such as e-healthcare, transportation, agriculture, stock market, etc. Advanced analytics is a mixture of machine learning, artificial intelligence, graphs, text mining, data mining, semantic analysis. It is an approach to data analysis. Beyond the traditional business intelligence, it is a semi and autonomous analysis of data by using different techniques and tools. However, deep learning and data analysis both are high centers of data science. Almost all the private and public organizations collect heavy amounts of data, i.e., domain-specific data. Many small/large companies are exploring large amounts of data for existing and future technology. Deep learning is also exploring large amounts of unsupervised data making it beneficial and effective for big data. Deep learning can be used to deal with all kinds of problems and challenges that include collecting unlabeled and uncategorized raw data, extracting complex patterns from a large amount of data, retrieving fast information, tagging data, etc. This book contains 16 chapters on artificial intelligence, machine learning, deep learning, and their uses in many useful sectors like stock market prediction, a recommendation system for better service selection, e-healthcare, telemedicine, transportation. There are also chapters on innovations and future opportunities with fog computing/cloud computing and artificial intelligence. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in healthcare, telemedicine, transportation, and the financial sector. The book will also be a great source for software engineers and advanced students who are beginners in the field of advanced analytics in deep learning.

Computer Vision and Recognition Systems

Chiranji Lal Chowdhary,G. Thippa Reddy,B. D. Parameshachari
Computer Vision and Recognition Systems Book PDF

Author : Chiranji Lal Chowdhary,G. Thippa Reddy,B. D. Parameshachari
Publisher : CRC Press
Page : 272 pages
File Size : 43,6 Mb
Release : 2022-03-10
Category : Science
ISBN : 9781000400779

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Computer Vision and Recognition Systems by Chiranji Lal Chowdhary,G. Thippa Reddy,B. D. Parameshachari Pdf

This cutting-edge volume focuses on how artificial intelligence can be used to give computers the ability to imitate human sight. With contributions from researchers in diverse countries, including Thailand, Spain, Japan, Turkey, Australia, and India, the book explains the essential modules that are necessary for comprehending artificial intelligence experiences to provide machines with the power of vision. The volume also presents innovative research developments, applications, and current trends in the field. The chapters cover such topics as visual quality improvement, Parkinson’s disease diagnosis, hypertensive retinopathy detection through retinal fundus, big image data processing, N-grams for image classification, medical brain images, chatbot applications, credit score improvisation, vision-based vehicle lane detection, damaged vehicle parts recognition, partial image encryption of medical images, and image synthesis. The chapter authors show different approaches to computer vision, image processing, and frameworks for machine learning to build automated and stable applications. Deep learning is included for making immersive application-based systems, pattern recognition, and biometric systems. The book also considers efficiency and comparison at various levels of using algorithms for real-time applications, processes, and analysis.

Artificial Intelligence Applications and Innovations

Ilias Maglogiannis,Lazaros Iliadis,Elias Pimenidis
Artificial Intelligence Applications and Innovations Book PDF

Author : Ilias Maglogiannis,Lazaros Iliadis,Elias Pimenidis
Publisher : Springer Nature
Page : 481 pages
File Size : 51,5 Mb
Release : 2020-05-29
Category : Computers
ISBN : 9783030491611

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Artificial Intelligence Applications and Innovations by Ilias Maglogiannis,Lazaros Iliadis,Elias Pimenidis Pdf

This 2 volume-set of IFIP AICT 583 and 584 constitutes the refereed proceedings of the 16th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2020, held in Neos Marmaras, Greece, in June 2020.* The 70 full papers and 5 short papers presented were carefully reviewed and selected from 149 submissions. They cover a broad range of topics related to technical, legal, and ethical aspects of artificial intelligence systems and their applications and are organized in the following sections: Part I: classification; clustering - unsupervised learning -analytics; image processing; learning algorithms; neural network modeling; object tracking - object detection systems; ontologies - AI; and sentiment analysis - recommender systems. Part II: AI ethics - law; AI constraints; deep learning - LSTM; fuzzy algebra - fuzzy systems; machine learning; medical - health systems; and natural language. *The conference was held virtually due to the COVID-19 pandemic.

Applied Deep Learning

Umberto Michelucci
Applied Deep Learning Book PDF

Author : Umberto Michelucci
Publisher : Apress
Page : 425 pages
File Size : 50,6 Mb
Release : 2018-09-07
Category : Computers
ISBN : 9781484237908

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Applied Deep Learning by Umberto Michelucci Pdf

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and Swish), seeing how to perform linear and logistic regression using TensorFlow, and choosing the right cost function. The next section talks about more complicated neural network architectures with several layers and neurons and explores the problem of random initialization of weights. An entire chapter is dedicated to a complete overview of neural network error analysis, giving examples of solving problems originating from variance, bias, overfitting, and datasets coming from different distributions. Applied Deep Learning also discusses how to implement logistic regression completely from scratch without using any Python library except NumPy, to let you appreciate how libraries such as TensorFlow allow quick and efficient experiments. Case studies for each method are included to put into practice all theoretical information. You’ll discover tips and tricks for writing optimized Python code (for example vectorizing loops with NumPy). What You Will Learn Implement advanced techniques in the right way in Python and TensorFlow Debug and optimize advanced methods (such as dropout and regularization) Carry out error analysis (to realize if one has a bias problem, a variance problem, a data offset problem, and so on) Set up a machine learning project focused on deep learning on a complex dataset Who This Book Is For Readers with a medium understanding of machine learning, linear algebra, calculus, and basic Python programming.

Artificial Intelligence Applications and Innovations

Lazaros Iliadis,Ilias Maglogiannis,Vassilis Plagianakos
Artificial Intelligence Applications and Innovations Book PDF

Author : Lazaros Iliadis,Ilias Maglogiannis,Vassilis Plagianakos
Publisher : Springer
Page : 649 pages
File Size : 49,9 Mb
Release : 2018-05-21
Category : Computers
ISBN : 9783319920078

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Artificial Intelligence Applications and Innovations by Lazaros Iliadis,Ilias Maglogiannis,Vassilis Plagianakos Pdf

This book constitutes the refereed proceedings of the 14th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2018, held in Rhodes, Greece, in May 2018. The 42 full papers and 12 short papers were carefully reviewed and selected from 88 submissions. They are organized in the following topical sections: social media, games, ontologies; deep learning; support vector machines; constraints; machine learning, regression, classification; neural networks; medical intelligence; recommender systems; optimization; learning, intelligence; heuristic approaches, cloud; fuzzy; and human and computer interaction, sound, video, processing.

Artificial Intelligence Applications and Innovations

John MacIntyre,Ilias Maglogiannis,Lazaros Iliadis,Elias Pimenidis
Artificial Intelligence Applications and Innovations Book PDF

Author : John MacIntyre,Ilias Maglogiannis,Lazaros Iliadis,Elias Pimenidis
Publisher : Springer
Page : 694 pages
File Size : 54,6 Mb
Release : 2019-05-15
Category : Computers
ISBN : 9783030198237

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Artificial Intelligence Applications and Innovations by John MacIntyre,Ilias Maglogiannis,Lazaros Iliadis,Elias Pimenidis Pdf

This book constitutes the refereed proceedings of the 15th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2019, held in Hersonissos, Crete, Greece, in May 2019. The 49 full papers and 6 short papers presented were carefully reviewed and selected from 101 submissions. They cover a broad range of topics such as deep learning ANN; genetic algorithms - optimization; constraints modeling; ANN training algorithms; social media intelligent modeling; text mining/machine translation; fuzzy modeling; biomedical and bioinformatics algorithms and systems; feature selection; emotion recognition; hybrid Intelligent models; classification - pattern recognition; intelligent security modeling; complex stochastic games; unsupervised machine learning; ANN in industry; intelligent clustering; convolutional and recurrent ANN; recommender systems; intelligent telecommunications modeling; and intelligent hybrid systems using Internet of Things. The papers are organized in the following topical sections:AI anomaly detection - active learning; autonomous vehicles - aerial vehicles; biomedical AI; classification - clustering; constraint programming - brain inspired modeling; deep learning - convolutional ANN; fuzzy modeling; learning automata - logic based reasoning; machine learning - natural language; multi agent - IoT; nature inspired flight and robot; control - machine vision; and recommendation systems.