Download or read book Implementation of Machine Learning Algorithms Using Control Flow and Dataflow Paradigms written by Milutinovi?, Veljko and published by IGI Global. This book was released on 2022-03-11 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Emerging Technologies for Innovation Management in the Software Industry written by Gupta, Varun and published by IGI Global. This book was released on 2022-05-20 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book New Approaches to Data Analytics and Internet of Things Through Digital Twin written by Karthikeyan, P. and published by IGI Global. This book was released on 2022-09-30 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Futuristic Trends for Sustainable Development and Sustainable Ecosystems written by Ortiz-Rodriguez, Fernando and published by IGI Global. This book was released on 2022-06-24 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Advances in Computers written by Suyel Namasudra and published by Academic Press. This book was released on 2022-03-24 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book High Performance Computing written by Rio Yokota and published by Springer. This book was released on 2019-01-24 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of 13 workshops held at the 33rd International ISC High Performance 2018 Conference, in Frankfurt, Germany, in June 2018: HPC I/O in the Data Center, HPC-IODC 2018; Workshop on Performance and Scalability of Storage Systems, WOPSSS 2018; 13th Workshop on Virtualization in High-Performance Cloud Computing, VHPC 2018; Third International Workshop on In Situ Visualization, WOIV 2018; 4th International Workshop on Communication Architectures for HPC, Big Data, Deep Learning and Clouds at Extreme Scale, ExaComm 2018; International Workshop on OpenPOWER for HPC, IWOPH 2018; IXPUG Workshop: Many-Core Computing on Intel Processors; Workshop on Sustainable Ultrascale Computing Systems; Approximate and Transprecision Computing on Emerging Technologies, ATCET 2018; First Workshop on the Convergence of Large-Scale Simulation and Artificial Intelligence; Third Workshop for Open Source Supercomputing, OpenSuCo 2018; First Workshop on Interactive High-Performance Computing; Workshop on Performance Portable Programming Models for Accelerators, P^3MA 2018. The 53 full papers included in this volume were carefully reviewed and selected from 80 submissions. They cover all aspects of research, development, and application of large-scale, high performance experimental and commercial systems. Topics include HPC computer architecture and hardware; programming models, system software, and applications; solutions for heterogeneity, reliability, power efficiency of systems; virtualization and containerized environments; big data and cloud computing; and artificial intelligence.
Download or read book Algorithms for Reinforcement Learning written by Csaba Szepesvari and published by Morgan & Claypool Publishers. This book was released on 2010-08-08 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Machine Learning Algorithms and Applications written by Mettu Srinivas and published by John Wiley & Sons. This book was released on 2021-08-24 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Machine Learning and Its Implementation written by Dr. M. Shanmukhi Marella and published by Blue Rose Publishers. This book was released on 2022-09-16 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will help the students and experienced professionals in understanding the concepts in a much easier way. As the book is more of a practical guide for implementing machine learning rather than just covering the concepts in a theoretical way. In this book, you’ll learn about how to create algorithms in machine learning. It teaches readers how to write code for algorithms. Thanks & Regards
Download or read book New Trends in Intelligent Software Methodologies Tools and Techniques written by H. Fujita and published by IOS Press. This book was released on 2017-09-07 with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Machine Learning Models and Algorithms for Big Data Classification written by Shan Suthaharan and published by Springer. This book was released on 2015-10-20 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of Research on Methodologies and Applications of Supercomputing written by Veljko Milutinovic and published by Engineering Science Reference. This book was released on 2021-02-19 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book offers a variety of perspectives and summarize the advances of control flow and data flow super computing, shedding light on selected emerging big data applications needing high acceleration and/or low power"--
Download or read book Machine Learning Using R written by Karthik Ramasubramanian and published by Apress. This book was released on 2019-01-04 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Proceedings written by and published by . This book was released on 2007 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Energy Research Abstracts written by and published by . This book was released on 1990 with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book DataFlow Supercomputing Essentials written by Veljko Milutinovic and published by Springer. This book was released on 2017-10-30 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This informative text/reference highlights the potential of DataFlow computing in research requiring high speeds, low power requirements, and high precision, while also benefiting from a reduction in the size of the equipment. The cutting-edge research and implementation case studies provided in this book will help the reader to develop their practical understanding of the advantages and unique features of this methodology. This work serves as a companion title to DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, which reviews the key algorithms in this area, and provides useful examples. Topics and features: reviews the library of tools, applications, and source code available to support DataFlow programming; discusses the enhancements to DataFlow computing yielded by small hardware changes, different compilation techniques, debugging, and optimizing tools; examines when a DataFlow architecture is best applied, and for which types of calculation; describes how converting applications to a DataFlow representation can result in an acceleration in performance, while reducing the power consumption; explains how to implement a DataFlow application on Maxeler hardware architecture, with links to a video tutorial series available online. This enlightening volume will be of great interest to all researchers investigating supercomputing in general, and DataFlow computing in particular. Advanced undergraduate and graduate students involved in courses on Data Mining, Microprocessor Systems, and VLSI Systems, will also find the book to be a helpful reference.
Download or read book SBCCI 2007 written by Antonio Petraglia and published by . This book was released on 2007 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
