Implementation Of Machine Learning Algorithms Using Control Flow And Dataflow Paradigms

Author : Milutinovi?, Veljko,Miti?, Nenad,Kartelj, Aleksandar,Kotlar, Miloš
Publisher : IGI Global
Page : 296 pages
File Size : 51,5 Mb
Release : 2022-03-11
Category : Computers
ISBN : 9781799883524

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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms by Milutinovi?, Veljko,Miti?, Nenad,Kartelj, Aleksandar,Kotlar, Miloš Pdf

Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

Author : Gupta, Varun,Gupta, Chetna
Publisher : IGI Global
Page : 282 pages
File Size : 53,9 Mb
Release : 2022-05-20
Category : Computers
ISBN : 9781799890614

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Emerging Technologies for Innovation Management in the Software Industry by Gupta, Varun,Gupta, Chetna Pdf

Innovation is the key to maintain competitive advantage. Innovation in products, processes, and business models help companies to provide economic value to their customers. Identifying the innovative ideas, implementing those ideas, and absorbing them in the market requires investing many resources that could incur large costs. Technology encourages companies to foster innovation to remain competitive in the marketplace. Emerging Technologies for Innovation Management in the Software Industry serves as a resource for technology absorption in companies supporting innovation. It highlights the role of technology to assist software companies—especially small start-ups—to innovate their products, processes, and business models. This book provides the necessary guidelines of which tools to use and under what situations. Covering topics such as risk management, prioritization approaches, and digitally-enabled innovation processes, this premier reference source is an ideal resource for entrepreneurs, software developers, software managers, business leaders, engineers, students and faculty of higher education, researchers, and academicians.

Author : Karthikeyan, P.,Katina, Polinpapilinho F.,Anandaraj, S.P.
Publisher : IGI Global
Page : 326 pages
File Size : 48,5 Mb
Release : 2022-09-30
Category : Computers
ISBN : 9781668457245

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New Approaches to Data Analytics and Internet of Things Through Digital Twin by Karthikeyan, P.,Katina, Polinpapilinho F.,Anandaraj, S.P. Pdf

Even though many data analytics tools have been developed in the past years, their usage in the field of cyber twin warrants new approaches that consider various aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real-time analysis, sampling, dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection. Further study is required to fully understand the opportunities, benefits, and difficulties of data analytics and the internet of things in today’s modern world. New Approaches to Data Analytics and Internet of Things Through Digital Twin considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. Covering key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Author : Ortiz-Rodriguez, Fernando,Tiwari, Sanju,Iyer, Sailesh,Medina-Quintero, José Melchor
Publisher : IGI Global
Page : 320 pages
File Size : 40,8 Mb
Release : 2022-06-24
Category : Business & Economics
ISBN : 9781668442272

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Futuristic Trends for Sustainable Development and Sustainable Ecosystems by Ortiz-Rodriguez, Fernando,Tiwari, Sanju,Iyer, Sailesh,Medina-Quintero, José Melchor Pdf

A key focus in recent years has been on sustainable development and promoting environmentally conscious practices. In today’s rapidly evolving technological world, it is important to consider how technology can be applied to solve problems across disciplines and fields in these areas. Further study is needed in order to understand how technology can be applied to sustainability and the best practices, considerations, and challenges that follow. Futuristic Trends for Sustainable Development and Sustainable Ecosystems discusses recent advances and innovative research in the area of information and communication technology for sustainable development and covers practices in several artificial intelligence fields such as knowledge representation and reasoning, natural language processing, machine learning, and the semantic web. Covering topics such as blockchain, deep learning, and renewable energy, this reference work is ideal for computer scientists, industry professionals, researchers, academicians, scholars, instructors, and students.

Author : Suyel Namasudra
Publisher : Academic Press
Page : 258 pages
File Size : 45,8 Mb
Release : 2022-03-24
Category : Mathematics
ISBN : 9780323988568

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Advances in Computers by Suyel Namasudra Pdf

Advances in Computers, Volume 126 presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on VLSI for Super-Computing: Creativity in R+D from Applications and Algorithms to Masks and Chips, Bulk Bitwise Execution Model in Memory: Mechanisms, Implementation, and Evaluation, Embracing the Laws of Physics: Three Reversible Models of Computation, WSNs in Environmental Monitoring: Data Acquisition and Dissemination Aspects, Energy efficient implementation of tensor operations using dataflow paradigm for machine learning, and A Run-Time Job Scheduling Algorithm for Cluster Architectures with DataFlow Accelerators. Contains novel subject matter that is relevant to computer science Includes the expertise of contributing authorsPresents an easy to comprehend writing style

Author : Alessandro Palmas,Emanuele Ghelfi,Dr. Alexandra Galina Petre,Mayur Kulkarni,Anand N.S.,Quan Nguyen,Aritra Sen,Anthony So,Saikat Basak
Publisher : Packt Publishing Ltd
Page : 821 pages
File Size : 42,7 Mb
Release : 2020-08-18
Category : Computers
ISBN : 9781800209961

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The The Reinforcement Learning Workshop by Alessandro Palmas,Emanuele Ghelfi,Dr. Alexandra Galina Petre,Mayur Kulkarni,Anand N.S.,Quan Nguyen,Aritra Sen,Anthony So,Saikat Basak Pdf

Start with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and policy-based methods with this practical guide Key FeaturesUse TensorFlow to write reinforcement learning agents for performing challenging tasksLearn how to solve finite Markov decision problemsTrain models to understand popular video games like BreakoutBook Description Various intelligent applications such as video games, inventory management software, warehouse robots, and translation tools use reinforcement learning (RL) to make decisions and perform actions that maximize the probability of the desired outcome. This book will help you to get to grips with the techniques and the algorithms for implementing RL in your machine learning models. Starting with an introduction to RL, you’ll be guided through different RL environments and frameworks. You’ll learn how to implement your own custom environments and use OpenAI baselines to run RL algorithms. Once you’ve explored classic RL techniques such as Dynamic Programming, Monte Carlo, and TD Learning, you’ll understand when to apply the different deep learning methods in RL and advance to deep Q-learning. The book will even help you understand the different stages of machine-based problem-solving by using DARQN on a popular video game Breakout. Finally, you’ll find out when to use a policy-based method to tackle an RL problem. By the end of The Reinforcement Learning Workshop, you’ll be equipped with the knowledge and skills needed to solve challenging problems using reinforcement learning. What you will learnUse OpenAI Gym as a framework to implement RL environmentsFind out how to define and implement reward functionExplore Markov chain, Markov decision process, and the Bellman equationDistinguish between Dynamic Programming, Monte Carlo, and Temporal Difference LearningUnderstand the multi-armed bandit problem and explore various strategies to solve itBuild a deep Q model network for playing the video game BreakoutWho this book is for If you are a data scientist, machine learning enthusiast, or a Python developer who wants to learn basic to advanced deep reinforcement learning algorithms, this workshop is for you. A basic understanding of the Python language is necessary.

Author : Csaba Szepesvari
Publisher : Morgan & Claypool Publishers
Page : 103 pages
File Size : 51,6 Mb
Release : 2010-08-08
Category : Technology & Engineering
ISBN : 9781608454938

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Algorithms for Reinforcement Learning by Csaba Szepesvari Pdf

Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations. Table of Contents: Markov Decision Processes / Value Prediction Problems / Control / For Further Exploration

Author : Mettu Srinivas,G. Sucharitha,Anjanna Matta
Publisher : John Wiley & Sons
Page : 372 pages
File Size : 53,7 Mb
Release : 2021-08-24
Category : Computers
ISBN : 9781119768852

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Machine Learning Algorithms and Applications by Mettu Srinivas,G. Sucharitha,Anjanna Matta Pdf

Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniques, with each chapter dealing with a novel approach of machine learning architecture for a specific application, and then compares the results with previous algorithms. The book discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, sentiment analysis, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the user can easily move from the equations in the book to a computer program.

Author : H. Fujita,A. Selamat,S. Omatu
Publisher : IOS Press
Page : 852 pages
File Size : 46,7 Mb
Release : 2017-09-07
Category : Computers
ISBN : 9781614998006

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New Trends in Intelligent Software Methodologies, Tools and Techniques by H. Fujita,A. Selamat,S. Omatu Pdf

Software is an essential enabler for science and the new economy. It creates new markets and directions for a more reliable, flexible and robust society and empowers the exploration of our world in ever more depth, but it often falls short of our expectations. Current software methodologies, tools, and techniques are still neither robust nor reliable enough for the constantly evolving market, and many promising approaches have so far failed to deliver the solutions required. This book presents the keynote ‘Engineering Cyber-Physical Systems’ and 64 peer-reviewed papers from the 16th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques, (SoMeT_17), held in Kitakyushu, Japan, in September 2017, which brought together researchers and practitioners to share original research results and practical development experience in software science and related new technologies. The aim of the SoMeT conferences is to capture the essence of the new state-of-the-art in software science and its supporting technology and to identify the challenges such technology will have to master. The book explores new trends and theories which illuminate the direction of developments in this field, and will be of interest to anyone whose work involves software science and its integration into tomorrow’s global information society.

Author : Karthik Ramasubramanian,Abhishek Singh
Publisher : Apress
Page : 545 pages
File Size : 52,6 Mb
Release : 2019-01-04
Category : Computers
ISBN : 1484242149

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Machine Learning Using R by Karthik Ramasubramanian,Abhishek Singh Pdf

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python if you are only comfortable with R. As in the first edition, the authors have kept the fine balance of theory and application of machine learning through various real-world use-cases which gives you a comprehensive collection of topics in machine learning. New chapters in this edition cover time series models and deep learning. What You'll Learn Understand machine learning algorithms using R Master the process of building machine-learning models Cover the theoretical foundations of machine-learning algorithms See industry focused real-world use cases Tackle time series modeling in R Apply deep learning using Keras and TensorFlow in R Who This Book is For Data scientists, data science professionals, and researchers in academia who want to understand the nuances of machine-learning approaches/algorithms in practice using R.

Author : Anonim
Publisher : Unknown
Page : 384 pages
File Size : 54,5 Mb
Release : 2007
Category : Integrated circuits
ISBN : UIUC:30112061325889

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Proceedings by Anonim Pdf

Author : Antonio Petraglia
Publisher : Unknown
Page : 384 pages
File Size : 48,8 Mb
Release : 2007
Category : Technology & Engineering
ISBN : STANFORD:36105133408695

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SBCCI 2007 by Antonio Petraglia Pdf

Author : Anonim
Publisher : Unknown
Page : 702 pages
File Size : 54,5 Mb
Release : 1995
Category : Aeronautics
ISBN : UIUC:30112048646605

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Scientific and Technical Aerospace Reports by Anonim Pdf

Author : Shan Suthaharan
Publisher : Springer
Page : 359 pages
File Size : 52,5 Mb
Release : 2015-10-20
Category : Business & Economics
ISBN : 9781489976413

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Machine Learning Models and Algorithms for Big Data Classification by Shan Suthaharan Pdf

This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.

Author : Albert Y. Zomaya,Sherif Sakr
Publisher : Springer
Page : 895 pages
File Size : 45,6 Mb
Release : 2017-02-25
Category : Computers
ISBN : 9783319493404

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Handbook of Big Data Technologies by Albert Y. Zomaya,Sherif Sakr Pdf

This handbook offers comprehensive coverage of recent advancements in Big Data technologies and related paradigms. Chapters are authored by international leading experts in the field, and have been reviewed and revised for maximum reader value. The volume consists of twenty-five chapters organized into four main parts. Part one covers the fundamental concepts of Big Data technologies including data curation mechanisms, data models, storage models, programming models and programming platforms. It also dives into the details of implementing Big SQL query engines and big stream processing systems. Part Two focuses on the semantic aspects of Big Data management including data integration and exploratory ad hoc analysis in addition to structured querying and pattern matching techniques. Part Three presents a comprehensive overview of large scale graph processing. It covers the most recent research in large scale graph processing platforms, introducing several scalable graph querying and mining mechanisms in domains such as social networks. Part Four details novel applications that have been made possible by the rapid emergence of Big Data technologies such as Internet-of-Things (IOT), Cognitive Computing and SCADA Systems. All parts of the book discuss open research problems, including potential opportunities, that have arisen from the rapid progress of Big Data technologies and the associated increasing requirements of application domains. Designed for researchers, IT professionals and graduate students, this book is a timely contribution to the growing Big Data field. Big Data has been recognized as one of leading emerging technologies that will have a major contribution and impact on the various fields of science and varies aspect of the human society over the coming decades. Therefore, the content in this book will be an essential tool to help readers understand the development and future of the field.