Learning Engineering Toolkit

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Author :
Publisher : Taylor & Francis
ISBN 13 : 1000683257
Total Pages : 477 pages
Book Rating : 4.0/5 (6 download)

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Book Synopsis Learning Engineering Toolkit by : Jim Goodell

Download or read book Learning Engineering Toolkit written by Jim Goodell and published by Taylor & Francis. This book was released on 2022-07-25 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Learning Engineering Toolkit is a practical guide to the rich and varied applications of learning engineering, a rigorous and fast-emerging discipline that synthesizes the learning sciences, instructional design, engineering design, and other methodologies to support learners. As learning engineering becomes an increasingly formalized discipline and practice, new insights and tools are needed to help education, training, design, and data analytics professionals iteratively develop, test, and improve complex systems for engaging and effective learning. Written in a colloquial style and full of collaborative, actionable strategies, this book explores the essential foundations, approaches, and real-world challenges inherent to ensuring participatory, data-driven, learning experiences across populations and contexts.

Design Recommendations for Intelligent Tutoring Systems: Volume 11 - Professional Career Education

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Publisher : U.S. Army Combat Capabilities Development Command – Soldier Center
ISBN 13 : 0997725850
Total Pages : 140 pages
Book Rating : 4.9/5 (977 download)

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Book Synopsis Design Recommendations for Intelligent Tutoring Systems: Volume 11 - Professional Career Education by : Anne Sinatra

Download or read book Design Recommendations for Intelligent Tutoring Systems: Volume 11 - Professional Career Education written by Anne Sinatra and published by U.S. Army Combat Capabilities Development Command – Soldier Center. This book was released on 2023-09-01 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Design Recommendations for Intelligent Tutoring Systems series has covered many different topics over the past ten years. Those topics have ranged from general components of intelligent tutoring systems (ITSs) (Learner Modeling, Instructional Management, Authoring Tools, Domain Modeling) to advanced elements (Assessment Methods, Team Tutoring, Self-Improving Systems, Data Visualization, Competency Based-Scenario Design). Our most recent previous volume included a series of Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analyses on all the initial topics as well as overviews of ITSs in general and the Generalized Intelligent Framework for Tutoring (GIFT) software (Sottilare et al., 2012; Sottilare et al., 2017; Goldberg & Sinatra, 2023). Each book in the Design Recommendations for Intelligent Tutoring Systems series has been associated with an Expert Workshop on the same topic. These workshops are part of a cooperative agreement (W911NF18-2-0039) between US Army Combat Capabilities Development Command (DEVCOM) Soldier Center and University of Memphis. One of the goals of the expert workshops is to learn more about ITS capabilities that are being developed, and how these approaches, as well as lessons learned, could enhance the GIFT software (GIFT is freely available at https://www.GIFTtutoring.org). Invited experts in industry, academia, and government discuss the expert workshop topic, their applicable work, and suggestions for improving GIFT in what is usually a two day event. Both the University of Memphis and GIFT Teams participate in the workshop, help to guide discussion, and ask questions that will provide insight into current challenges in GIFT. The expert workshop associated with this current book was held virtually in October 2022, and included presentations about both general approaches and specific applications to professional education in ITSs. Additionally, the University of Memphis team that participated in the workshop included Arthur C. Graesser, Xiangen Hu, Vasile Rus, and Jody Cockroft. The US Army DEVCOM Soldier Center team who participated in the workshop included Benjamin Goldberg, Gregory Goodwin, Anne M. Sinatra, Randall Spain, and Lisa N. Townsend. The current volume and the expert workshop that was associated with it, branched out in a new direction and rather than addressing specific components of an ITS or types of features/approaches that could be included in ITSs, it focused on how to apply an ITS for specific types of training. The specific focus was on ITSs for Professional Career Education. This topic area was selected, as in general, ITS research tends to be focused on K-12 or college education, and in many cases on domains such as algebra or physics. However, for the military, and for industry, trainees are adult learners and domains tend to be more active, applied, and experiential. This workshop provided an opportunity for discussion of specific examples of applied training that occurs with ITSs, as well as discussion of general approaches and considerations for applied professional education in ITSs.

Machine Learning Engineering in Action

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Author :
Publisher : Simon and Schuster
ISBN 13 : 1638356580
Total Pages : 879 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Machine Learning Engineering in Action by : Ben Wilson

Download or read book Machine Learning Engineering in Action written by Ben Wilson and published by Simon and Schuster. This book was released on 2022-05-17 with total page 879 pages. Available in PDF, EPUB and Kindle. Book excerpt: Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production. In Machine Learning Engineering in Action, you will learn: Evaluating data science problems to find the most effective solution Scoping a machine learning project for usage expectations and budget Process techniques that minimize wasted effort and speed up production Assessing a project using standardized prototyping work and statistical validation Choosing the right technologies and tools for your project Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices Ferrying a machine learning project from your data science team to your end users is no easy task. Machine Learning Engineering in Action will help you make it simple. Inside, you'll find fantastic advice from veteran industry expert Ben Wilson, Principal Resident Solutions Architect at Databricks. Ben introduces his personal toolbox of techniques for building deployable and maintainable production machine learning systems. You'll learn the importance of Agile methodologies for fast prototyping and conferring with stakeholders, while developing a new appreciation for the importance of planning. Adopting well-established software development standards will help you deliver better code management, and make it easier to test, scale, and even reuse your machine learning code. Every method is explained in a friendly, peer-to-peer style and illustrated with production-ready source code. About the technology Deliver maximum performance from your models and data. This collection of reproducible techniques will help you build stable data pipelines, efficient application workflows, and maintainable models every time. Based on decades of good software engineering practice, machine learning engineering ensures your ML systems are resilient, adaptable, and perform in production. About the book Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects. You'll discover software engineering techniques like conducting experiments on your prototypes and implementing modular design that result in resilient architectures and consistent cross-team communication. Based on the author's extensive experience, every method in this book has been used to solve real-world projects. What's inside Scoping a machine learning project for usage expectations and budget Choosing the right technologies for your design Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices About the reader For data scientists who know machine learning and the basics of object-oriented programming. About the author Ben Wilson is Principal Resident Solutions Architect at Databricks, where he developed the Databricks Labs AutoML project, and is an MLflow committer.

An Elegant Puzzle

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Author :
Publisher : Stripe Press
ISBN 13 : 1953953336
Total Pages : 281 pages
Book Rating : 4.9/5 (539 download)

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Book Synopsis An Elegant Puzzle by : Will Larson

Download or read book An Elegant Puzzle written by Will Larson and published by Stripe Press. This book was released on 2019-05-20 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: A human-centric guide to solving complex problems in engineering management, from sizing teams to handling technical debt. There’s a saying that people don’t leave companies, they leave managers. Management is a key part of any organization, yet the discipline is often self-taught and unstructured. Getting to the good solutions for complex management challenges can make the difference between fulfillment and frustration for teams—and, ultimately, between the success and failure of companies. Will Larson’s An Elegant Puzzle focuses on the particular challenges of engineering management—from sizing teams to handling technical debt to performing succession planning—and provides a path to the good solutions. Drawing from his experience at Digg, Uber, and Stripe, Larson has developed a thoughtful approach to engineering management for leaders of all levels at companies of all sizes. An Elegant Puzzle balances structured principles and human-centric thinking to help any leader create more effective and rewarding organizations for engineers to thrive in.

Crosscutting Concepts

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Publisher : National Science Teachers Association
ISBN 13 : 9781681407289
Total Pages : 0 pages
Book Rating : 4.4/5 (72 download)

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Book Synopsis Crosscutting Concepts by : Jeffrey Nordine

Download or read book Crosscutting Concepts written by Jeffrey Nordine and published by National Science Teachers Association. This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "If you've been trying to figure out how crosscutting concepts (CCCs) fit into three-dimensional learning, this in-depth resource will show you their usefulness across the sciences. Crosscutting Concepts: Strengthening Science and Engineering Learning is designed to help teachers at all grade levels (1) promote students' sensemaking and problem-solving abilities by integrating CCCs with science and engineering practices and disciplinary core ideas; (2) support connections across multiple disciplines and diverse contexts; and (3) use CCCs as a set of lenses through which students can learn about the world around them. The book is divided into the following four sections. Foundational issues that undergird crosscutting concepts. You'll see how CCCs can change your instruction, engage your students in science, and broaden access and inclusion for all students in the science classroom. An in-depth look at individual CCCs. You'll learn to use each CCC across disciplines, understand the challenges students face in learning CCCs, and adopt exemplary teaching strategies. Ways to use CCCs to strengthen how you teach key topics in science. These topics include the nature of matter, plant growth, and weather and climate, as well as engineering design. Ways that CCCs can enhance the work of science teaching. These topics include student assessment and teacher professional collaboration. Throughout the book, vignettes drawn from the authors' own classroom experiences will help you put theory into practice. Instructional Applications show how CCCs can strengthen your planning. Classroom Snapshots offer practical ways to use CCCs in discussions and lessons. No matter how you use this book to enrich your thinking, it will help you leverage the power of CCCs to strengthen students' science and engineering learning. As the book says, "CCCs can often provide deeper insight into phenomena and problems by providing complementary perspectives that both broaden and sharpen our view on the rapidly changing world that students will inherit.""--

Educational Data Science

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Publisher : Springer Nature
ISBN 13 : 9819900263
Total Pages : 299 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Educational Data Science by : Alejandro Peña-Ayala

Download or read book Educational Data Science written by Alejandro Peña-Ayala and published by Springer Nature. This book was released on 2023 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments. This is why diverse researchers and scholars contribute with valuable chapters to ground with well-sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic reviews, reveals valuable insights, and promotes its application to extend its practice. EDS as a transdisciplinary field relies on statistics, probability, machine learning, data mining, and analytics, in addition to biological, psychological, and neurological knowledge about learning science. With this in mind, the book is devoted to those that are in charge of educational management, educators, pedagogues, academics, computer technologists, researchers, and postgraduate students, who pursue to acquire a conceptual, formal, and practical landscape of how to deploy EDS to build proactive, real- time, and reactive applications that personalize education, enhance teaching, and improve learning!

Fundamentals and Frontiers of Medical Education and Decision-Making

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Author :
Publisher : Taylor & Francis
ISBN 13 : 1040048544
Total Pages : 339 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Fundamentals and Frontiers of Medical Education and Decision-Making by : Jordan Richard Scheonherr

Download or read book Fundamentals and Frontiers of Medical Education and Decision-Making written by Jordan Richard Scheonherr and published by Taylor & Francis. This book was released on 2024-07-22 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals and Frontiers of Medical Education and Decision-Making brings together international experts to consider the theoretical, practical, and sociocultural foundations of health professions education. In this volume, the authors review the foundational theories that have informed the early transition to competency-based education. Moving beyond these monolithic models, the authors draw from learning and psychological sciences to provide a means to operationalize competencies. The chapters cover fundamental topics including the transition from novices to experts, the development of psychomotor skills in surgery, the role of emotion and metacognition in decision-making, and how practitioners and laypeople represent and communicate health information. Each section provides chapters that integrate and advance our understanding of health professions education and decision- making. Grounded in psychological science, this book highlights the fundamental issues faced by healthcare professionals, and the frontiers of learning and decision-making. It is important reading for a wide audience of healthcare professionals, healthcare administrators, as well as researchers in judgment and decision-making.

Machine Learning Engineering with Python

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1837634351
Total Pages : 463 pages
Book Rating : 4.8/5 (376 download)

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Book Synopsis Machine Learning Engineering with Python by : Andrew P. McMahon

Download or read book Machine Learning Engineering with Python written by Andrew P. McMahon and published by Packt Publishing Ltd. This book was released on 2023-08-31 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transform your machine learning projects into successful deployments with this practical guide on how to build and scale solutions that solve real-world problems Includes a new chapter on generative AI and large language models (LLMs) and building a pipeline that leverages LLMs using LangChain Key Features This second edition delves deeper into key machine learning topics, CI/CD, and system design Explore core MLOps practices, such as model management and performance monitoring Build end-to-end examples of deployable ML microservices and pipelines using AWS and open-source tools Book DescriptionThe Second Edition of Machine Learning Engineering with Python is the practical guide that MLOps and ML engineers need to build solutions to real-world problems. It will provide you with the skills you need to stay ahead in this rapidly evolving field. The book takes an examples-based approach to help you develop your skills and covers the technical concepts, implementation patterns, and development methodologies you need. You'll explore the key steps of the ML development lifecycle and create your own standardized "model factory" for training and retraining of models. You'll learn to employ concepts like CI/CD and how to detect different types of drift. Get hands-on with the latest in deployment architectures and discover methods for scaling up your solutions. This edition goes deeper in all aspects of ML engineering and MLOps, with emphasis on the latest open-source and cloud-based technologies. This includes a completely revamped approach to advanced pipelining and orchestration techniques. With a new chapter on deep learning, generative AI, and LLMOps, you will learn to use tools like LangChain, PyTorch, and Hugging Face to leverage LLMs for supercharged analysis. You will explore AI assistants like GitHub Copilot to become more productive, then dive deep into the engineering considerations of working with deep learning.What you will learn Plan and manage end-to-end ML development projects Explore deep learning, LLMs, and LLMOps to leverage generative AI Use Python to package your ML tools and scale up your solutions Get to grips with Apache Spark, Kubernetes, and Ray Build and run ML pipelines with Apache Airflow, ZenML, and Kubeflow Detect drift and build retraining mechanisms into your solutions Improve error handling with control flows and vulnerability scanning Host and build ML microservices and batch processes running on AWS Who this book is for This book is designed for MLOps and ML engineers, data scientists, and software developers who want to build robust solutions that use machine learning to solve real-world problems. If you’re not a developer but want to manage or understand the product lifecycle of these systems, you’ll also find this book useful. It assumes a basic knowledge of machine learning concepts and intermediate programming experience in Python. With its focus on practical skills and real-world examples, this book is an essential resource for anyone looking to advance their machine learning engineering career.

Knowledge Engineering Tools and Techniques for AI Planning

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Author :
Publisher : Springer Nature
ISBN 13 : 3030385612
Total Pages : 275 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Knowledge Engineering Tools and Techniques for AI Planning by : Mauro Vallati

Download or read book Knowledge Engineering Tools and Techniques for AI Planning written by Mauro Vallati and published by Springer Nature. This book was released on 2020-03-25 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive review for Knowledge Engineering tools and techniques that can be used in Artificial Intelligence Planning and Scheduling. KE tools can be used to aid in the acquisition of knowledge and in the construction of domain models, which this book will illustrate. AI planning engines require a domain model which captures knowledge about how a particular domain works - e.g. the objects it contains and the available actions that can be used. However, encoding a planning domain model is not a straightforward task - a domain expert may be needed for their insight into the domain but this information must then be encoded in a suitable representation language. The development of such domain models is both time-consuming and error-prone. Due to these challenges, researchers have developed a number of automated tools and techniques to aid in the capture and representation of knowledge. This book targets researchers and professionals working in knowledge engineering, artificial intelligence and software engineering. Advanced-level students studying AI will also be interested in this book.

Adaptive Instructional Systems. Design and Evaluation

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Publisher : Springer Nature
ISBN 13 : 3030778576
Total Pages : 649 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Adaptive Instructional Systems. Design and Evaluation by : Robert A. Sottilare

Download or read book Adaptive Instructional Systems. Design and Evaluation written by Robert A. Sottilare and published by Springer Nature. This book was released on 2021-07-03 with total page 649 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 12792 and 12793 constitutes the refereed proceedings of the Third International Conference on Adaptive Instructional Systems, AIS 2021, held as Part of the 23rd International Conference, HCI International 2021, which took place in July 2021. Due to COVID-19 pandemic the conference was held virtually. The total of 1276 papers and 241 posters included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions. The papers of AIS 2021, Part I, are organized in topical sections named: Conceptual Models and Instructional Approaches for AIS; Designing and Developing AIS; Evaluation of AIS; Adaptation Strategies and Methods in AIS. Chapter “Personalized Mastery Learning Ecosystems: Using Bloom’s Four Objects of Change to Drive Learning in Adaptive Instructional Systems” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Learning Chaos Engineering

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492050954
Total Pages : 166 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Learning Chaos Engineering by : Russ Miles

Download or read book Learning Chaos Engineering written by Russ Miles and published by "O'Reilly Media, Inc.". This book was released on 2019-07-12 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most companies work hard to avoid costly failures, but in complex systems a better approach is to embrace and learn from them. Through chaos engineering, you can proactively hunt for evidence of system weaknesses before they trigger a crisis. This practical book shows software developers and system administrators how to plan and run successful chaos engineering experiments. System weaknesses go beyond your infrastructure, platforms, and applications to include policies, practices, playbooks, and people. Author Russ Miles explains why, when, and how to test systems, processes, and team responses using simulated failures on Game Days. You’ll also learn how to work toward continuous chaos through automation with features you can share across your team and organization. Learn to think like a chaos engineer Build a hypothesis backlog to determine what could go wrong in your system Develop your hypotheses into chaos engineering experiment Game Days Write, run, and learn from automated chaos experiments using the open source Chaos Toolkit Turn chaos experiments into tests to confirm that you’ve overcome the weaknesses you discovered Observe and control your automated chaos experiments while they are running

HCI International 2022 – Late Breaking Posters

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Publisher : Springer Nature
ISBN 13 : 3031196821
Total Pages : 739 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis HCI International 2022 – Late Breaking Posters by : Constantine Stephanidis

Download or read book HCI International 2022 – Late Breaking Posters written by Constantine Stephanidis and published by Springer Nature. This book was released on 2022-11-23 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume CCIS 1655 is part of the refereed proceedings of the 24th International Conference on Human-Computer Interaction, HCII 2022, which was held virtually during June 26 to July 1, 2022. A total of 5583 individuals from academia, research institutes, industry, and governmental agencies from 88 countries submitted contributions, and 1276 papers and 275 posters were included in the proceedings that were published just before the start of the conference. Additionally, 296 papers and 181 posters are included in the volumes of the proceedings published after the conference, as “Late Breaking Work” (papers and posters). The contributions thoroughly cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas.

Machine Learning for Healthcare Applications

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1119791812
Total Pages : 418 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning for Healthcare Applications by : Sachi Nandan Mohanty

Download or read book Machine Learning for Healthcare Applications written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2021-04-13 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.

Product Engineering

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Publisher : Springer Science & Business Media
ISBN 13 : 1402082002
Total Pages : 569 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Product Engineering by : Doru Talaba

Download or read book Product Engineering written by Doru Talaba and published by Springer Science & Business Media. This book was released on 2008-04-06 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains an edited version of the lectures and selected contributions presented during the Advanced Summer Institute (ASI) on "Product Engineering: Tools and Methods based on Virtual Reality" held at Chania (Greece), 30th May - 6th June 2007. The ASI was devoted to the Product Engineering field, with particular attention being given to the aspects related to Virtual Reality (VR) technologies, and their use and added value in engineering.

Putting AI in the Critical Loop

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Author :
Publisher : Elsevier
ISBN 13 : 0443159874
Total Pages : 306 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Putting AI in the Critical Loop by : Prithviraj Dasgupta

Download or read book Putting AI in the Critical Loop written by Prithviraj Dasgupta and published by Elsevier. This book was released on 2024-02-20 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a high level of autonomy for a human-machine team requires assumptions that address behavior and mutual trust. The performance of a human-machine team is maximized when the partnership provides mutual benefits that satisfy design rationales, balance of control, and the nature of autonomy. The distinctively different characteristics and features of humans and machines are likely why they have the potential to work well together, overcoming each other's weaknesses through cooperation, synergy, and interdependence which forms a "collective intelligence. Trust is bidirectional and two-sided; humans need to trust AI technology, but future AI technology may also need to trust humans.Putting AI in the Critical Loop: Assured Trust and Autonomy in Human-Machine Teams focuses on human-machine trust and "assured performance and operation in order to realize the potential of autonomy. This book aims to take on the primary challenges of bidirectional trust and performance of autonomous systems, providing readers with a review of the latest literature, the science of autonomy, and a clear path towards the autonomy of human-machine teams and systems. Throughout this book, the intersecting themes of collective intelligence, bidirectional trust, and continual assurance form the challenging and extraordinarily interesting themes which will help lay the groundwork for the audience to not only bridge the knowledge gaps, but also to advance this science to develop better solutions. - Assesses the latest research advances, engineering challenges, and the theoretical gaps surrounding the question of autonomy - Reviews the challenges of autonomy (e.g., trust, ethics, legalities, etc.), including gaps in the knowledge of the science - Offers a path forward to solutions - Investigates the value of trust by humans of HMTs, as well as the bidirectionality of trust, understanding how machines learn to trust their human teammates

Radical Solutions and Learning Analytics

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Author :
Publisher : Springer Nature
ISBN 13 : 981154526X
Total Pages : 233 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Radical Solutions and Learning Analytics by : Daniel Burgos

Download or read book Radical Solutions and Learning Analytics written by Daniel Burgos and published by Springer Nature. This book was released on 2020-05-08 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning Analytics become the key for Personalised Learning and Teaching thanks to the storage, categorisation and smart retrieval of Big Data. Thousands of user data can be tracked online via Learning Management Systems, instant messaging channels, social networks and other ways of communication. Always with the explicit authorisation from the end user, being a student, a teacher, a manager or a persona in a different role, an instructional designer can design a way to produce a practical dashboard that helps him improve that very user’s performance, interaction, motivation or just grading. This book provides a thorough approach on how education, as such, from teaching to learning through management, is improved by a smart analysis of available data, making visible and useful behaviours, predictions and patterns that are hinder to the regular eye without the process of massive data.

Proceedings of the 11th Annual Generalized Intelligent Framework for Tutoring (GIFT) Users Symposium (GIFTSym11)

Download Proceedings of the 11th Annual Generalized Intelligent Framework for Tutoring (GIFT) Users Symposium (GIFTSym11) PDF Online Free

Author :
Publisher : U.S. Army Combat Capabilities Development Command – Soldier Center
ISBN 13 : 0997725842
Total Pages : 178 pages
Book Rating : 4.9/5 (977 download)

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Book Synopsis Proceedings of the 11th Annual Generalized Intelligent Framework for Tutoring (GIFT) Users Symposium (GIFTSym11) by : Benjamin Goldberg

Download or read book Proceedings of the 11th Annual Generalized Intelligent Framework for Tutoring (GIFT) Users Symposium (GIFTSym11) written by Benjamin Goldberg and published by U.S. Army Combat Capabilities Development Command – Soldier Center. This book was released on 2023-07-01 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to the Proceedings of the 11th Annual GIFT User Symposium! This year we are celebrating 11 years of GIFT Symposiums and have accepted 15 papers for publication. All of the presentations that occurred at GIFTSym11, and the papers in this volume show the versatility of the Generalized Intelligent Framework for Tutoring (GIFT), and the work that is being done with GIFT. GIFT is an open-source intelligent tutoring system (ITS) architecture that is freely available online at GIFTtutoring.org. There are both Cloud and Downloadable version of GIFT. GIFT has been developed with multiple goals in mind including supporting ITS research, and simplified creation of ITSs and Adaptive Instructional Systems (AISs). Our fantastic team, and our program committee did a great job supporting the development of GIFTSym11, reviewing papers, and assisting with the facilitation of the event this year. We want to recognize them for their efforts: • Benjamin Goldberg • Gregory Goodwin • Michele Myers • Alexandra Lutz • Randall Spain • Lisa N. Townsend We were very pleased to have GIFTSym11 return to being an in-person event this year! Additionally, this was our first year offering a hybrid option for attendees. We are very happy that both modalities were well attended!