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Author: Deanne Henry
Publisher:
Published: 2004
Total Pages: 173
ISBN-13: 9780973536508
DOWNLOAD EBOOKDownload or read book Streamlining : the First Line Learning Technique written by Deanne Henry and published by . This book was released on 2004 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author: Wankel, Charles
Publisher: IGI Global
Published: 2011-06-30
Total Pages: 492
ISBN-13: 1609608011
DOWNLOAD EBOOK"This book is both a snapshot of streaming media in higher education as it is today and a window into the many developments already underway, forecasting of areas yet to be developed"-- Provided by publisher.
Download or read book Streaming Media Delivery in Higher Education: Methods and Outcomes written by Wankel, Charles and published by IGI Global. This book was released on 2011-06-30 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is both a snapshot of streaming media in higher education as it is today and a window into the many developments already underway, forecasting of areas yet to be developed"-- Provided by publisher.
Author: Miriam B. Larson
Publisher: Routledge
Published: 2019-12-09
Total Pages: 595
ISBN-13: 1351258702
DOWNLOAD EBOOKStreamlined ID presents a focused and generalizable approach to instructional design and development – one that addresses the needs of ID novices as well as practitioners in a variety of career environments. Highlighting essentials and big ideas, this guide advocates a streamlined approach to instructional design: producing instruction that is sustainable, optimized, appropriately redundant, and targeted at continuous improvement. The book’s enhanced version of the classic ADDIE model (Analysis, Design, Development, Implementation, and Evaluation) emphasizes the iterative nature of design and the role of evaluation throughout the design/development process. It clearly lays out a systematic approach that emphasizes the use of research-based theories, while acknowledging the need to customize the process to accommodate a variety of pedagogical approaches. This thoroughly revised second edition reflects recent advances and changes in the field, adds three new chapters, updates reference charts, job aids, and tips to support practitioners working in a variety of career environments, and speaks more clearly than ever to ID novices and graduate students.
Download or read book Streamlined ID written by Miriam B. Larson and published by Routledge. This book was released on 2019-12-09 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Streamlined ID presents a focused and generalizable approach to instructional design and development – one that addresses the needs of ID novices as well as practitioners in a variety of career environments. Highlighting essentials and big ideas, this guide advocates a streamlined approach to instructional design: producing instruction that is sustainable, optimized, appropriately redundant, and targeted at continuous improvement. The book’s enhanced version of the classic ADDIE model (Analysis, Design, Development, Implementation, and Evaluation) emphasizes the iterative nature of design and the role of evaluation throughout the design/development process. It clearly lays out a systematic approach that emphasizes the use of research-based theories, while acknowledging the need to customize the process to accommodate a variety of pedagogical approaches. This thoroughly revised second edition reflects recent advances and changes in the field, adds three new chapters, updates reference charts, job aids, and tips to support practitioners working in a variety of career environments, and speaks more clearly than ever to ID novices and graduate students.
Author: Gerard Maas
Publisher: O'Reilly Media
Published: 2019-06-05
Total Pages: 453
ISBN-13: 1491944218
DOWNLOAD EBOOKBefore you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. You’ll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs. Authors Gerard Maas and François Garillot help you explore the theoretical underpinnings of Apache Spark. This comprehensive guide features two sections that compare and contrast the streaming APIs Spark now supports: the original Spark Streaming library and the newer Structured Streaming API. Learn fundamental stream processing concepts and examine different streaming architectures Explore Structured Streaming through practical examples; learn different aspects of stream processing in detail Create and operate streaming jobs and applications with Spark Streaming; integrate Spark Streaming with other Spark APIs Learn advanced Spark Streaming techniques, including approximation algorithms and machine learning algorithms Compare Apache Spark to other stream processing projects, including Apache Storm, Apache Flink, and Apache Kafka Streams
Download or read book Stream Processing with Apache Spark written by Gerard Maas and published by O'Reilly Media. This book was released on 2019-06-05 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: Before you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. You’ll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs. Authors Gerard Maas and François Garillot help you explore the theoretical underpinnings of Apache Spark. This comprehensive guide features two sections that compare and contrast the streaming APIs Spark now supports: the original Spark Streaming library and the newer Structured Streaming API. Learn fundamental stream processing concepts and examine different streaming architectures Explore Structured Streaming through practical examples; learn different aspects of stream processing in detail Create and operate streaming jobs and applications with Spark Streaming; integrate Spark Streaming with other Spark APIs Learn advanced Spark Streaming techniques, including approximation algorithms and machine learning algorithms Compare Apache Spark to other stream processing projects, including Apache Storm, Apache Flink, and Apache Kafka Streams
Author: Jim Thompson
Publisher: Productive Publications
Published: 2014-05-14
Total Pages: 139
ISBN-13: 1552705463
DOWNLOAD EBOOKDownload or read book THE LEAN OFFICE: How to Use Just-in-Time Techniques to Streamline Your Office written by Jim Thompson and published by Productive Publications. This book was released on 2014-05-14 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author: Jesús Medina
Publisher: Springer
Published: 2018-05-30
Total Pages: 835
ISBN-13: 3319914731
DOWNLOAD EBOOKThis three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).
Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations written by Jesús Medina and published by Springer. This book was released on 2018-05-30 with total page 835 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).
Author: K. Gayathri Devi
Publisher: CRC Press
Published: 2022-05-11
Total Pages: 351
ISBN-13: 1000583368
DOWNLOAD EBOOKThe application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).
Download or read book Machine Learning and Deep Learning Techniques for Medical Science written by K. Gayathri Devi and published by CRC Press. This book was released on 2022-05-11 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).
Author: Mrs.S.N.Santhalakshmi
Publisher: Leilani Katie Publication
Published: 2024-05-16
Total Pages: 185
ISBN-13: 9363489655
DOWNLOAD EBOOKMrs.S.N.Santhalakshmi, Assistant Professor & Head of The Department, Department of Computer Applications, Nandha Arts & Science College, Erode, Tamil Nadu, India. Dr.Goutam Panigrahi, Assistant Professor, Department of Mathematics, National Institute of Technology, Durgapur, West Bengal, India. Dr. Saibal Majumder, Assistant Professor, Department of Computer Science and Engineering(Data Science), Dr. B.C. Roy Engineering College, Durgapur, West Bengal, India. Dr. Chandan Bandyopadhyay, Associate Professor & Head of the Department, Department of Computer Science and Engineering(Data Science), Dr. B.C. Roy Engineering College, Durgapur, West Bengal, India.
Download or read book Machine Learning: A Gateway to Data Science written by Mrs.S.N.Santhalakshmi and published by Leilani Katie Publication. This book was released on 2024-05-16 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mrs.S.N.Santhalakshmi, Assistant Professor & Head of The Department, Department of Computer Applications, Nandha Arts & Science College, Erode, Tamil Nadu, India. Dr.Goutam Panigrahi, Assistant Professor, Department of Mathematics, National Institute of Technology, Durgapur, West Bengal, India. Dr. Saibal Majumder, Assistant Professor, Department of Computer Science and Engineering(Data Science), Dr. B.C. Roy Engineering College, Durgapur, West Bengal, India. Dr. Chandan Bandyopadhyay, Associate Professor & Head of the Department, Department of Computer Science and Engineering(Data Science), Dr. B.C. Roy Engineering College, Durgapur, West Bengal, India.
Author: Guozhu Dong
Publisher: CRC Press
Published: 2018-03-14
Total Pages: 389
ISBN-13: 1351721267
DOWNLOAD EBOOKFeature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achieved if there are few features to represent the underlying data objects, and the quality of results of those algorithms largely depends on the quality of the available features. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive introduction to feature engineering, including feature generation, feature extraction, feature transformation, feature selection, and feature analysis and evaluation. The book presents key concepts, methods, examples, and applications, as well as chapters on feature engineering for major data types such as texts, images, sequences, time series, graphs, streaming data, software engineering data, Twitter data, and social media data. It also contains generic feature generation approaches, as well as methods for generating tried-and-tested, hand-crafted, domain-specific features. The first chapter defines the concepts of features and feature engineering, offers an overview of the book, and provides pointers to topics not covered in this book. The next six chapters are devoted to feature engineering, including feature generation for specific data types. The subsequent four chapters cover generic approaches for feature engineering, namely feature selection, feature transformation based feature engineering, deep learning based feature engineering, and pattern based feature generation and engineering. The last three chapters discuss feature engineering for social bot detection, software management, and Twitter-based applications respectively. This book can be used as a reference for data analysts, big data scientists, data preprocessing workers, project managers, project developers, prediction modelers, professors, researchers, graduate students, and upper level undergraduate students. It can also be used as the primary text for courses on feature engineering, or as a supplement for courses on machine learning, data mining, and big data analytics.
Download or read book Feature Engineering for Machine Learning and Data Analytics written by Guozhu Dong and published by CRC Press. This book was released on 2018-03-14 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achieved if there are few features to represent the underlying data objects, and the quality of results of those algorithms largely depends on the quality of the available features. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive introduction to feature engineering, including feature generation, feature extraction, feature transformation, feature selection, and feature analysis and evaluation. The book presents key concepts, methods, examples, and applications, as well as chapters on feature engineering for major data types such as texts, images, sequences, time series, graphs, streaming data, software engineering data, Twitter data, and social media data. It also contains generic feature generation approaches, as well as methods for generating tried-and-tested, hand-crafted, domain-specific features. The first chapter defines the concepts of features and feature engineering, offers an overview of the book, and provides pointers to topics not covered in this book. The next six chapters are devoted to feature engineering, including feature generation for specific data types. The subsequent four chapters cover generic approaches for feature engineering, namely feature selection, feature transformation based feature engineering, deep learning based feature engineering, and pattern based feature generation and engineering. The last three chapters discuss feature engineering for social bot detection, software management, and Twitter-based applications respectively. This book can be used as a reference for data analysts, big data scientists, data preprocessing workers, project managers, project developers, prediction modelers, professors, researchers, graduate students, and upper level undergraduate students. It can also be used as the primary text for courses on feature engineering, or as a supplement for courses on machine learning, data mining, and big data analytics.
Author: H. James Harrington
Publisher: McGraw Hill Professional
Published: 2011-08-05
Total Pages: 430
ISBN-13: 0071770968
DOWNLOAD EBOOK“The Business Process Improvement methodology established by Dr. H. James Harrington and his group brings revolutionary improvement not only in quality of products and services, but also in the business processes.” —Professor Yoshio Kondo The Book That Goes Beyond Six Sigma and Lean . . . The Next Evolutionary Step in Business Process Management “Don’t design for Six Sigma—design for maximum performance.” H. James Harrington How would you like to streamline your operations, lower your costs, improve your quality, and increase your profits—all at the same time? It’s not an impossible dream. It’s the next evolutionary breakthrough in process improvement that goes beyond Process Reengineering, TRIZ, Six Sigma, and Lean to deliver actual, quantifiable results. And now it’s yours. Streamlined Process Improvement (SPI) is the powerful new program developed by H. James Harrington. After 40 years of improving processes for IBM, Ernst & Young, the Chinese government, and many other private and governmental organizations, Harrington has become the go-to leader in the field. His revolutionary guide shows you how to: Discover the latest process tools—to make faster, more dramatic improvements using the revolutionary PASIC improvement methodology Use walk-through questionnaires and checklists—to streamline your job, resulting in optimum value to your stakeholders Use the newest methodologies—including simulation modeling, risk analysis, Five Ss, Process Innovation, Information Technology, Lean, and Six Sigma—to take your business to the next level Increase innovation—to drive growth and profits for many years to come Harrington’s groundbreaking system is organized and explained step by step to help you achieve maximum results with a minimum of stress. His simple PASIC approach shows you how to Plan, Analyze, Streamline, Implement, and Continuously Improve throughout the entire process. He walks you through the basics of how to analyze each process, how to decide which to focus on first, and how to prepare for organizational change. You’ll be surprised by just how quickly you can make things run more efficiently and effectively. With Harrington’s proven techniques, you can sell your products and services at a lower price, satisfy your customers, make work more enjoyable for your employees, and still earn greater profits than your competitors. This powerful process guide is the definitive handbook for operations managers, quality consultants, Six Sigma practitioners, knowledge workers, and Lean thinkers for a new generation.
Download or read book Streamlined Process Improvement written by H. James Harrington and published by McGraw Hill Professional. This book was released on 2011-08-05 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: “The Business Process Improvement methodology established by Dr. H. James Harrington and his group brings revolutionary improvement not only in quality of products and services, but also in the business processes.” —Professor Yoshio Kondo The Book That Goes Beyond Six Sigma and Lean . . . The Next Evolutionary Step in Business Process Management “Don’t design for Six Sigma—design for maximum performance.” H. James Harrington How would you like to streamline your operations, lower your costs, improve your quality, and increase your profits—all at the same time? It’s not an impossible dream. It’s the next evolutionary breakthrough in process improvement that goes beyond Process Reengineering, TRIZ, Six Sigma, and Lean to deliver actual, quantifiable results. And now it’s yours. Streamlined Process Improvement (SPI) is the powerful new program developed by H. James Harrington. After 40 years of improving processes for IBM, Ernst & Young, the Chinese government, and many other private and governmental organizations, Harrington has become the go-to leader in the field. His revolutionary guide shows you how to: Discover the latest process tools—to make faster, more dramatic improvements using the revolutionary PASIC improvement methodology Use walk-through questionnaires and checklists—to streamline your job, resulting in optimum value to your stakeholders Use the newest methodologies—including simulation modeling, risk analysis, Five Ss, Process Innovation, Information Technology, Lean, and Six Sigma—to take your business to the next level Increase innovation—to drive growth and profits for many years to come Harrington’s groundbreaking system is organized and explained step by step to help you achieve maximum results with a minimum of stress. His simple PASIC approach shows you how to Plan, Analyze, Streamline, Implement, and Continuously Improve throughout the entire process. He walks you through the basics of how to analyze each process, how to decide which to focus on first, and how to prepare for organizational change. You’ll be surprised by just how quickly you can make things run more efficiently and effectively. With Harrington’s proven techniques, you can sell your products and services at a lower price, satisfy your customers, make work more enjoyable for your employees, and still earn greater profits than your competitors. This powerful process guide is the definitive handbook for operations managers, quality consultants, Six Sigma practitioners, knowledge workers, and Lean thinkers for a new generation.
