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Learning Metrics
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Book Synopsis Learning Metrics by : Ajay Pangarkar
Download or read book Learning Metrics written by Ajay Pangarkar and published by Kogan Page Publishers. This book was released on 2024-05-03 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: How do I know if Learning and Development (L&D) initiatives are making a difference to employee and business performance? What should I measure and how do I take a data-driven approach? Learning Metrics is a practical book for L&D professionals which answers these questions and provides guidance for measuring and communicating the impact of L&D activity in the business. It covers how to measure participant engagement with learning, learning retention and changes in employee performance post-learning. There is also guidance on how to measure on-the-job behaviour change as a result of learning, as well as metrics for measuring the organizational impact of learning. This book also has essential guidance on how to use learning analytics to assess the return on investment (ROI) of learning and how to use these results to adopt a data-driven approach and map learning metrics to organizational KPIs. Learning Metrics also includes guidance on how to communicate the impact of the company's learning and development activity to all business stakeholders. Full of practical guidance, examples, advice and case studies from organizations including Pfizer, Goldman Sachs, HSBC, Merck and Hewlett Packard, this is essential reading for all L&D professionals needing to measure the impact of L&D activity in the business but not sure where to start.
Download or read book Metric Learning written by Aurélien Muise and published by Springer Nature. This book was released on 2022-05-31 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: Similarity between objects plays an important role in both human cognitive processes and artificial systems for recognition and categorization. How to appropriately measure such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of interest in machine learning and related fields in the past ten years. In this book, we provide a thorough review of the metric learning literature that covers algorithms, theory and applications for both numerical and structured data. We first introduce relevant definitions and classic metric functions, as well as examples of their use in machine learning and data mining. We then review a wide range of metric learning algorithms, starting with the simple setting of linear distance and similarity learning. We show how one may scale-up these methods to very large amounts of training data. To go beyond the linear case, we discuss methods that learn nonlinear metrics or multiple linear metrics throughout the feature space, and review methods for more complex settings such as multi-task and semi-supervised learning. Although most of the existing work has focused on numerical data, we cover the literature on metric learning for structured data like strings, trees, graphs and time series. In the more technical part of the book, we present some recent statistical frameworks for analyzing the generalization performance in metric learning and derive results for some of the algorithms presented earlier. Finally, we illustrate the relevance of metric learning in real-world problems through a series of successful applications to computer vision, bioinformatics and information retrieval. Table of Contents: Introduction / Metrics / Properties of Metric Learning Algorithms / Linear Metric Learning / Nonlinear and Local Metric Learning / Metric Learning for Special Settings / Metric Learning for Structured Data / Generalization Guarantees for Metric Learning / Applications / Conclusion / Bibliography / Authors' Biographies
Download or read book Imbalanced Learning written by Haibo He and published by John Wiley & Sons. This book was released on 2013-06-07 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data. Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, defense, and more. Due to the inherent complex characteristics of imbalanced data sets, learning from such data requires new understandings, principles, algorithms, and tools to transform vast amounts of raw data efficiently into information and knowledge representation. The first comprehensive look at this new branch of machine learning, this book offers a critical review of the problem of imbalanced learning, covering the state of the art in techniques, principles, and real-world applications. Featuring contributions from experts in both academia and industry, Imbalanced Learning: Foundations, Algorithms, and Applications provides chapter coverage on: Foundations of Imbalanced Learning Imbalanced Datasets: From Sampling to Classifiers Ensemble Methods for Class Imbalance Learning Class Imbalance Learning Methods for Support Vector Machines Class Imbalance and Active Learning Nonstationary Stream Data Learning with Imbalanced Class Distribution Assessment Metrics for Imbalanced Learning Imbalanced Learning: Foundations, Algorithms, and Applications will help scientists and engineers learn how to tackle the problem of learning from imbalanced datasets, and gain insight into current developments in the field as well as future research directions.
Download or read book Metrics 2.0 written by Ruth A. Huwe and published by Bloomsbury Publishing USA. This book was released on 2010-04-15 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This one-stop handbook gives managers who have been charged with creating metric scorecards techniques that will make them truly effective. Written for managers who want/need to create and use scorecards, Metrics 2.0: Creating Scorecards for High-Performance Work Teams and Organizations provides a unique perspective on this vital management tool. Focusing on performance improvement, it describes the intellectual foundation behind scorecards and demonstrates how metrics can be used to enhance feedback, motivation, and employee engagement. The book offers a background primer on statistics and research methods, outlining the basics of metrics such as attributes, scope of measures, and levels of analysis to help managers understand what should go into the scorecard and why. Key techniques for using scorecards are showcased and step-by-step guidance on creating metric scorecards for teams, departments, and entire organizations is provided, including specialized situations such as customer service measurement or monitoring off-site performance. Finally, managers are taught how to analyze results intelligently and translate metrics into effective operational practices. Extensive running examples address both service and manufacturing metrics and each chapter ends with a set of learning objectives.
Book Synopsis The Tyranny of Metrics by : Jerry Z. Muller
Download or read book The Tyranny of Metrics written by Jerry Z. Muller and published by Princeton University Press. This book was released on 2019-04-30 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: How the obsession with quantifying human performance threatens business, medicine, education, government—and the quality of our lives Today, organizations of all kinds are ruled by the belief that the path to success is quantifying human performance, publicizing the results, and dividing up the rewards based on the numbers. But in our zeal to instill the evaluation process with scientific rigor, we've gone from measuring performance to fixating on measuring itself—and this tyranny of metrics now threatens the quality of our organizations and lives. In this brief, accessible, and powerful book, Jerry Muller uncovers the damage metrics are causing and shows how we can begin to fix the problem. Filled with examples from business, medicine, education, government, and other fields, the book explains why paying for measured performance doesn't work, why surgical scorecards may increase deaths, and much more. But Muller also shows that, when used as a complement to judgment based on personal experience, metrics can be beneficial, and he includes an invaluable checklist of when and how to use them. The result is an essential corrective to a harmful trend that increasingly affects us all.
Book Synopsis Metric Learning by : Aurelien Bellet
Download or read book Metric Learning written by Aurelien Bellet and published by Morgan & Claypool Publishers. This book was released on 2015-01-01 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Similarity between objects plays an important role in both human cognitive processes and artificial systems for recognition and categorization. How to appropriately measure such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of interest in machine learning and related fields in the past ten years. In this book, we provide a thorough review of the metric learning literature that covers algorithms, theory and applications for both numerical and structured data. We first introduce relevant definitions and classic metric functions, as well as examples of their use in machine learning and data mining. We then review a wide range of metric learning algorithms, starting with the simple setting of linear distance and similarity learning. We show how one may scale-up these methods to very large amounts of training data. To go beyond the linear case, we discuss methods that learn nonlinear metrics or multiple linear metrics throughout the feature space, and review methods for more complex settings such as multi-task and semi-supervised learning. Although most of the existing work has focused on numerical data, we cover the literature on metric learning for structured data like strings, trees, graphs and time series. In the more technical part of the book, we present some recent statistical frameworks for analyzing the generalization performance in metric learning and derive results for some of the algorithms presented earlier. Finally, we illustrate the relevance of metric learning in real-world problems through a series of successful applications to computer vision, bioinformatics and information retrieval.
Book Synopsis Using Cognitive and Affective Metrics in Educational Simulations and Games by : Harold F. O'Neil
Download or read book Using Cognitive and Affective Metrics in Educational Simulations and Games written by Harold F. O'Neil and published by Taylor & Francis. This book was released on 2021-05-17 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting original studies and rich conceptual analyses, this volume explores how cognitive and affective metrics can be used to effectively assess, modify, and enhance learning and assessment outcomes of simulations and games used in education and training. The volume responds to the increasing use of computer-based simulations and games across academic and professional sectors by bringing together contributions from different research communities, including K-12 and postsecondary education, medical, and military contexts. Drawing on empirical results, the chapter authors focus on the design and assessment of educational simulations and games. They describe how quantitative and qualitative metrics can be used effectively to evaluate and tailor instructional resources to the cognitive and affective needs of the individual learner. In doing so, the volume enhances understanding of how games and simulations can intersect with the science of learning to improve educational outcomes. Given its rigorous and multidisciplinary approach, this book will prove an indispensable resource for researchers and scholars in the fields of educational assessment and evaluation, educational technology, military psychology, and educational psychology.
Book Synopsis Imbalanced Classification with Python by : Jason Brownlee
Download or read book Imbalanced Classification with Python written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2020-01-14 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Imbalanced classification are those classification tasks where the distribution of examples across the classes is not equal. Cut through the equations, Greek letters, and confusion, and discover the specialized techniques data preparation techniques, learning algorithms, and performance metrics that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently develop robust models for your own imbalanced classification projects.
Download or read book Overview: MELQO written by UNESCO and published by UNESCO Publishing. This book was released on 2017-08-14 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Measuring Early Learning Quality and Outcomes (MELQO) initiative began in 2014 as part of the global emphasis on early childhood development (ECD). Led by UNESCO, the World Bank, the Center for Universal Education at the Brookings Institution and UNICEF, the initiative aims to promote feasible, accurate and useful measurement of childrenâs development and learning at the start of primary school, and of the quality of their pre-primary learning environments. Items are designed for children between the ages of 4 and 6 years. Following the premise that many existing tools include similar items, the leading organizationsâ core team worked with a consortium of experts, non-governmental organizations (NGOs) and multilaterals to build upon current measurement tools to create a common set of items organized into modules for measuring: 1) early childhood development and learning, and 2) the quality of pre-primary learning environments. The MELQO core team and experts also collaborated to outline a process for context-specific adaptation of the measurement modules resulting from lessons learned from field-testing in several countries in 2015 and 2016. The modules are designed to be implemented at scale, with an emphasis on feasibility for low- and middle-income countries (LMICs). A key question addressed by MELQO was the balance between a global tool suitable for use everywhere, and local priorities and goals for childrenâs development. [Introduction, ed]
Book Synopsis A Look at Metrics in Distributive Education by : Robert A. Canei
Download or read book A Look at Metrics in Distributive Education written by Robert A. Canei and published by . This book was released on 1979 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Metric Learning written by Brian Kulis and published by Now Pub. This book was released on 2013 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metric Learning: A Review presents an overview of existing research in metric learning, including recent progress on scaling to high-dimensional feature spaces and to data sets with an extremely large number of data points. It presents as unified a framework as possible under which existing research on metric learning can be cast.
Book Synopsis Mastering 'Metrics by : Joshua D. Angrist
Download or read book Mastering 'Metrics written by Joshua D. Angrist and published by Princeton University Press. This book was released on 2014-12-21 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible and fun guide to the essential tools of econometric research Applied econometrics, known to aficionados as 'metrics, is the original data science. 'Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. Through accessible discussion and with a dose of kung fu–themed humor, Mastering 'Metrics presents the essential tools of econometric research and demonstrates why econometrics is exciting and useful. The five most valuable econometric methods, or what the authors call the Furious Five--random assignment, regression, instrumental variables, regression discontinuity designs, and differences in differences--are illustrated through well-crafted real-world examples (vetted for awesomeness by Kung Fu Panda's Jade Palace). Does health insurance make you healthier? Randomized experiments provide answers. Are expensive private colleges and selective public high schools better than more pedestrian institutions? Regression analysis and a regression discontinuity design reveal the surprising truth. When private banks teeter, and depositors take their money and run, should central banks step in to save them? Differences-in-differences analysis of a Depression-era banking crisis offers a response. Could arresting O. J. Simpson have saved his ex-wife's life? Instrumental variables methods instruct law enforcement authorities in how best to respond to domestic abuse. Wielding econometric tools with skill and confidence, Mastering 'Metrics uses data and statistics to illuminate the path from cause to effect. Shows why econometrics is important Explains econometric research through humorous and accessible discussion Outlines empirical methods central to modern econometric practice Works through interesting and relevant real-world examples
Book Synopsis Grokking Machine Learning by : Luis Serrano
Download or read book Grokking Machine Learning written by Luis Serrano and published by Simon and Schuster. This book was released on 2021-12-14 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Grokking Machine Learning presents machine learning algorithms and techniques in a way that anyone can understand. This book skips the confused academic jargon and offers clear explanations that require only basic algebra. As you go, you'll build interesting projects with Python, including models for spam detection and image recognition. You'll also pick up practical skills for cleaning and preparing data.
Book Synopsis The Metrics of Teacher Effectiveness and Teacher Quality Research by : Andrew Skourdoumbis
Download or read book The Metrics of Teacher Effectiveness and Teacher Quality Research written by Andrew Skourdoumbis and published by Routledge. This book was released on 2020-03-05 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most developed nations measure the performance of teachers in audit evaluations of school productivity. Accountability metrics such as "teacher effectiveness" and "teacher quality" dominate evaluations of student outcomes and shape education policy. The Metrics of Teacher Effectiveness and Teacher Quality Research explores how these metrics distort analyses of student achievement, sideline broader contextual and systemic influences on learning, reinforce input-output analysis of schooling, and skew the educational debate. Focusing on recent phases of school education policy reform, this book utilizes qualitative data from classroom teacher participants to examine how and why issues of teacher effectiveness and teacher quality figure so prominently in policy reform and why pressing matters of social class, school funding, and broader contextual influences are downplayed. The authors use this information to suggest how teachers can develop their role as pedagogic experts in a highly scrutinized environment. This book will be of great interest to education academics and postgraduate students specializing in teacher performance, accountability and governance.
Book Synopsis Software Metrics by : C. Ravindranath Pandian
Download or read book Software Metrics written by C. Ravindranath Pandian and published by CRC Press. This book was released on 2003-09-26 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modern field of software metrics emerged from the computer modeling and "statistical thinking" services of the 1980s. As the field evolved, metrics programs were integrated with project management, and metrics grew to be a major tool in the managerial decision-making process of software companies. Now practitioners in the software industry have
Download or read book Resources in Education written by and published by . This book was released on 1977 with total page 1100 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Metrics of Sensory Motor Coordination and Integration in Robots and Animals by : Fabio Bonsignorio
Download or read book Metrics of Sensory Motor Coordination and Integration in Robots and Animals written by Fabio Bonsignorio and published by Springer. This book was released on 2019-03-23 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on a critical issue in the study of physical agents, whether natural or artificial: the quantitative modelling of sensory–motor coordination. Adopting a novel approach, it defines a common scientific framework for both the intelligent systems designed by engineers and those that have evolved naturally. As such it contributes to the widespread adoption of a rigorous quantitative and refutable approach in the scientific study of ‘embodied’ intelligence and cognition. More than 70 years after Norbert Wiener’s famous book Cybernetics: or Control and Communication in the Animal and the Machine (1948), robotics, AI and life sciences seem to be converging towards a common model of what we can call the ‘science of embodied intelligent/cognitive agents’. This book is interesting for an interdisciplinary community of researchers, technologists and entrepreneurs working at the frontiers of robotics and AI, neuroscience and general life and brain sciences.