| confident adaptive language modeling: Generative AI in Teaching and Learning Hai-Jew, Shalin, 2023-12-05 Generative AI in Teaching and Learning delves into the revolutionary field of generative artificial intelligence and its impact on education. This comprehensive guide explores the multifaceted applications of generative AI in both formal and informal learning environments, shedding light on the ethical considerations and immense opportunities that arise from its implementation. From the early approaches of utilizing generative AI in teaching to its integration into various facets of learning, this book offers a profound analysis of its potential. Teachers, researchers, instructional designers, developers, data analysts, programmers, and learners alike will find valuable insights into harnessing the power of generative AI for educational purposes. |
| confident adaptive language modeling: Computational Linguistics and Intelligent Text Processing Alexander Gelbukh, 2023-02-25 The two-volume set LNCS 13451 and 13452 constitutes revised selected papers from the CICLing 2019 conference which took place in La Rochelle, France, April 2019. The total of 95 papers presented in the two volumes was carefully reviewed and selected from 335 submissions. The book also contains 3 invited papers. The papers are organized in the following topical sections: General, Information extraction, Information retrieval, Language modeling, Lexical resources, Machine translation, Morphology, sintax, parsing, Name entity recognition, Semantics and text similarity, Sentiment analysis, Speech processing, Text categorization, Text generation, and Text mining. |
| confident adaptive language modeling: Language as a Complex Adaptive System Nick C. Ellis, Diane Larsen-Freeman, 2009-12-30 Explores a new approach to studying language as a complex adaptive system, illustrating its commonalities across many areas of language research Brings together a team of leading researchers in linguistics, psychology, and complex systems to discuss the groundbreaking significance of this perspective for their work Illustrates its application across a variety of subfields, including languages usage, language evolution, language structure, and first and second language acquisition What a breath of fresh air! As interesting a collection of papers as you are likely to find on the evolution, learning, and use of language from the point of view of both cognitive underpinnings and communicative functions. Michael Tomasello, Max Planck Institute for Evolutionary Anthropology |
| confident adaptive language modeling: The Adaptive Value of Languages: Non-Linguistic Causes of Language Diversity Antonio Benítez-Burraco, Steven Moran, 2018-11-08 The goal of this eBook is to shed light on the non-linguistic causes of language diversity, and in particular, to explore the possibility that some aspects of the structure of languages may result from an adaptation to the natural and/or human-made environment. Traditionally, language diversity has been claimed to result from random, internally-motivated changes in language structure. However, ongoing research suggests instead that different factors that are external to language can promote language change and ultimately account for aspects of language diversity, specifically features of the social and physical environments. The contributions in this eBook discuss whether some aspects of languages are an adaptation to ecological, social, or even technological niches. |
| confident adaptive language modeling: Large Language Models in Cybersecurity Andrei Kucharavy, 2024 This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful large language models (LLMs) and how they can be mitigated. It attempts to outrun the malicious attackers by anticipating what they could do. It also alerts LLM developers to understand their work's risks for cybersecurity and provides them with tools to mitigate those risks. The book starts in Part I with a general introduction to LLMs and their main application areas. Part II collects a description of the most salient threats LLMs represent in cybersecurity, be they as tools for cybercriminals or as novel attack surfaces if integrated into existing software. Part III focuses on attempting to forecast the exposure and the development of technologies and science underpinning LLMs, as well as macro levers available to regulators to further cybersecurity in the age of LLMs. Eventually, in Part IV, mitigation techniques that should allowsafe and secure development and deployment of LLMs are presented. The book concludes with two final chapters in Part V, one speculating what a secure design and integration of LLMs from first principles would look like and the other presenting a summary of the duality of LLMs in cyber-security. This book represents the second in a series published by the Technology Monitoring (TM) team of the Cyber-Defence Campus. The first book entitled Trends in Data Protection and Encryption Technologies appeared in 2023. This book series provides technology and trend anticipation for government, industry, and academic decision-makers as well as technical experts. |
| confident adaptive language modeling: Deep Learning Ian Goodfellow, Yoshua Bengio, Aaron Courville, 2016-11-10 An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors. |
| confident adaptive language modeling: Humantech Marketing: o marketing molecular e humano Carlos Manuel de Oliveira, 2023-04-20 A exponencial evolução das tecnologias de comunicação e informação tem gerado, e continuará a gerar, impactos significativos na gestão de marketing. O marketing molecular e humano constitui a resposta a esta evolução. Este é o novo marketing polarizado no Ser Humano, fruto de um novo mindset empresarial e da possibilidade tecnológica de antecipar, criar e personalizar, em tempo real, experiências imersivas e memoráveis, que possam exceder as expectativas de relacionamento de cada cliente, com uma empresa ou marca, gerando maior fidelização. |
| confident adaptive language modeling: User Modeling, Adaption, and Personalization Sandra Carberry, Stephan Weibelzahl, Alessandro Micarelli, Giovanni Semeraro, 2013-06-05 This book constitutes the thoroughly refereed proceedings of the 21st International Conference on User Modeling, Adaption, and Personalization, held in Rome, Italy, in June 2013. The 21 long and 7 short papers of the research paper track were carefully reviewed and selected from numerous submissions. The papers cover the following topics: recommender systems, student modeling, social media and teams, human cognition, personality, privacy, web curation and user profiles, travel and mobile applications, and systems for elderly and disabled individuals. |
| confident adaptive language modeling: An Introduction to Sports Coaching Robyn L. Jones, Kieran Kingston, 2013-03-05 An Introduction to Sports Coaching provides students with an accessible and engaging guide to the scientific, social scientific, medical and pedagogical theory that underlies the practice of quality sports coaching. Now in a fully updated and revised second edition, it introduces students to the complex, messy, multi-faceted nature of coaching, and explores the full range of ‘knowledges’ which inform all successful coaching practice. Written by a team of leading international sports coaching academics and practitioners, as well as sport scientists and social scientists, the book provides a concise guide to every key theme in sports coaching, including: Reflective practice Pedagogy Skill acquisition Psychology Biomechanics Physiology Sport medicine and injury Performance analysis Sociology History Philosophy Sport development Each chapter makes a clear link between theory and practice, and includes discussion of real-life coaching scenarios and insights from practising international and club coaches. The book includes clear definitions of important themes and concepts, as well as seminar and review questions in each chapter designed to confirm understanding and encourage further enquiry. No other introductory textbook explains the importance of an holistic approach to sports coaching practice. This is an essential companion to any sports coaching course. |
| confident adaptive language modeling: The Emotional Rollercoaster of Language Teaching Christina Gkonou, Jean-Marc Dewaele, Jim King, 2020-05-19 This book focuses on the emotional complexity of language teaching and how the diverse emotions that teachers experience while teaching are shaped and function. The book is based on the premise that teaching is not just about the transmission of academic knowledge but also about inspiring students, building rapport with them, creating relationships based on empathy and trust, being patient and most importantly controlling one’s own emotions and being able to influence students’ emotions in a positive way. The book covers a range of emotion-related topics on both positive and negative emotions which are relevant to language teaching including emotional labour, burnout, emotion regulation, resilience, emotional intelligence and wellbeing among others. These topics are studied within a wide range of contexts such as teacher education programmes, tertiary education, CLIL and action research settings, and primary and secondary schools across different countries. The book will appeal to any student, researcher, teacher or policymaker who is interested in research on the psychological aspects of foreign language teaching. |
| confident adaptive language modeling: Social Robotics Abdulaziz Al Ali, John-John Cabibihan, Nader Meskin, Silvia Rossi, Wanyue Jiang, Hongsheng He, Shuzhi Sam Ge, 2024-01-03 The two-volume set LNAI 14453 and 14454 constitutes the refereed post-conference proceedings of the 15th International Conference on Social Robotics, ICSR 2023, held in Doha, Qatar, during December 4–7, 2023. The 68 revised full papers presented in these proceedings were carefully reviewed and selected from 83 submissions. They deal with topics around the interaction between humans and intelligent robots and on the integration of robots into the fabric of society. This year the special topic is Human-Robot Collaboration: Sea; Air; Land; Space and Cyberspace”, focusing on all physical and cyber-physical domains where humans and robots collaborate. |
| confident adaptive language modeling: European Control Conference 1993 , 1993-06-28 Proceedings of the European Control Conference 1993, Groningen, Netherlands, June 28 – July 1, 1993 |
| confident adaptive language modeling: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor, 2023-09-30 The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learning – explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications – abdomen; clinical applications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular; Part VIII: Clinical applications – neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration. |
| confident adaptive language modeling: An Introduction to Sports Coaching Robyn L. Jones, Kieran Kingston, 2013-03-05 An Introduction to Sports Coaching provides students with an accessible and engaging guide to the scientific, social scientific, medical and pedagogical theory that underlies the practice of quality sports coaching. Now in a fully updated and revised second edition, it introduces students to the complex, messy, multi-faceted nature of coaching, and explores the full range of ‘knowledges’ which inform all successful coaching practice. Written by a team of leading international sports coaching academics and practitioners, as well as sport scientists and social scientists, the book provides a concise guide to every key theme in sports coaching, including: Reflective practice Pedagogy Skill acquisition Psychology Biomechanics Physiology Sport medicine and injury Performance analysis Sociology History Philosophy Sport development Each chapter makes a clear link between theory and practice, and includes discussion of real-life coaching scenarios and insights from practising international and club coaches. The book includes clear definitions of important themes and concepts, as well as seminar and review questions in each chapter designed to confirm understanding and encourage further enquiry. No other introductory textbook explains the importance of an holistic approach to sports coaching practice. This is an essential companion to any sports coaching course. |
| confident adaptive language modeling: Statistical Inference as Severe Testing Deborah G. Mayo, 2018-09-20 Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification. |
| confident adaptive language modeling: Interpretable Machine Learning Christoph Molnar, 2020 This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project. |
| confident adaptive language modeling: Human-in-the-Loop Machine Learning Robert Munro, Robert Monarch, 2021-07-20 Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-loop machine learning lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to dreate training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows. |
| confident adaptive language modeling: Natural Language Understanding and Intelligent Applications Chin-Yew Lin, Nianwen Xue, Dongyan Zhao, Xuanjing Huang, Yansong Feng, 2016-11-30 This book constitutes the joint refereed proceedings of the 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and the 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, held in Kunming, China, in December 2016. The 48 revised full papers presented together with 41 short papers were carefully reviewed and selected from 216 submissions. The papers cover fundamental research in language computing, multi-lingual access, web mining/text mining, machine learning for NLP, knowledge graph, NLP for social network, as well as applications in language computing. |
| confident adaptive language modeling: Deep Reinforcement Learning Hands-On Maxim Lapan, 2020-01-31 Revised and expanded to include multi-agent methods, discrete optimization, RL in robotics, advanced exploration techniques, and more Key Features Second edition of the bestselling introduction to deep reinforcement learning, expanded with six new chapters Learn advanced exploration techniques including noisy networks, pseudo-count, and network distillation methods Apply RL methods to cheap hardware robotics platforms Book DescriptionDeep Reinforcement Learning Hands-On, Second Edition is an updated and expanded version of the bestselling guide to the very latest reinforcement learning (RL) tools and techniques. It provides you with an introduction to the fundamentals of RL, along with the hands-on ability to code intelligent learning agents to perform a range of practical tasks. With six new chapters devoted to a variety of up-to-the-minute developments in RL, including discrete optimization (solving the Rubik's Cube), multi-agent methods, Microsoft's TextWorld environment, advanced exploration techniques, and more, you will come away from this book with a deep understanding of the latest innovations in this emerging field. In addition, you will gain actionable insights into such topic areas as deep Q-networks, policy gradient methods, continuous control problems, and highly scalable, non-gradient methods. You will also discover how to build a real hardware robot trained with RL for less than $100 and solve the Pong environment in just 30 minutes of training using step-by-step code optimization. In short, Deep Reinforcement Learning Hands-On, Second Edition, is your companion to navigating the exciting complexities of RL as it helps you attain experience and knowledge through real-world examples.What you will learn Understand the deep learning context of RL and implement complex deep learning models Evaluate RL methods including cross-entropy, DQN, actor-critic, TRPO, PPO, DDPG, D4PG, and others Build a practical hardware robot trained with RL methods for less than $100 Discover Microsoft s TextWorld environment, which is an interactive fiction games platform Use discrete optimization in RL to solve a Rubik s Cube Teach your agent to play Connect 4 using AlphaGo Zero Explore the very latest deep RL research on topics including AI chatbots Discover advanced exploration techniques, including noisy networks and network distillation techniques Who this book is for Some fluency in Python is assumed. Sound understanding of the fundamentals of deep learning will be helpful. This book is an introduction to deep RL and requires no background in RL |
| confident adaptive language modeling: Handbook Of Pattern Recognition And Computer Vision (6th Edition) Chi Hau Chen, 2020-04-04 Written by world-renowned authors, this unique compendium presents the most updated progress in pattern recognition and computer vision (PRCV), fully reflecting the strong international research interests in the artificial intelligence arena.Machine learning has been the key to current developments in PRCV. This useful comprehensive volume complements the previous five editions of the book. It places great emphasis on the use of deep learning in many aspects of PRCV applications, not readily available in other reference text. |
| confident adaptive language modeling: Advanced Applications of Generative AI and Natural Language Processing Models Obaid, Ahmed J., Bhushan, Bharat, S., Muthmainnah, Rajest, S. Suman, 2023-12-21 The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Modelsequips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving. |
| confident adaptive language modeling: Normative Language Policy Leigh Oakes, Yael Peled, 2017-12-14 Language politics in the new global era presents policymakers with significant ethical challenges. How should the reality of English as a global language influence the normative considerations underpinning national language policies? What moral arguments justify the imposition of national languages in an era of increased immigration and ethnolinguistic diversity? What role is there for non-dominant varieties in a globalised world? Building on the emerging notion of 'normative language policy', this book proposes an integrated framework for the study of such questions, combining recent normative work on language in political theory and philosophy with empirically-derived insight from the fields of sociolinguistics and applied linguistics. The case of Quebec forms the backdrop of the study, providing a particularly illuminating setting for investigating the common moral challenges that face contemporary polities seeking to maintain distinct linguistic identities, in an irreducibly diverse world increasingly dominated by English as a global lingua franca. |
| confident adaptive language modeling: The Domestication of Language Daniel Cloud, 2014-11-25 Language did not evolve only in the distant past. Our shared understanding of the meanings of words is ever-changing, and we make conscious, rational decisions about which words to use and what to mean by them every day. Applying DarwinÕs theory of Òunconscious artificial selectionÓ to the evolution of linguistic conventions, Daniel Cloud suggests a new, evolutionary explanation for the rich, complex, and continually reinvented meanings of our words. The choice of which words to use and in which sense to use them is both a Òselection eventÓ and an intentional decision, making DarwinÕs account of artificial selection a particularly compelling model of the evolution of words. After drawing an analogy between the theory of domestication offered by Darwin and the evolution of human languages and cultures, Cloud applies his analytical framework to the question of what makes humans unique, and how they became that way. He incorporates insights from David LewisÕs Convention, Brian SkyrmsÕs Signals, and Kim SterelnyÕs Evolved Apprentice, all while emphasizing the role of deliberate human choice in the crafting of language over time. His clever and intuitive model casts humansÕ cultural and linguistic evolution as an integrated, dynamic process, with results that reach into all corners of our private lives and public character. |
| confident adaptive language modeling: Algorithmic Learning in a Random World Vladimir Vovk, Alexander Gammerman, Glenn Shafer, 2005-03-22 Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on these approximations, a new set of machine learning algorithms have been developed that can be used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data are independent and identically distributed (assumption of randomness). Another aim of this unique monograph is to outline some limits of predictions: The approach based on algorithmic theory of randomness allows for the proof of impossibility of prediction in certain situations. The book describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness. |
| confident adaptive language modeling: Statistical Rethinking Richard McElreath, 2018-01-03 Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas. |
| confident adaptive language modeling: Text Generation Kathleen McKeown, 1992-06-26 Kathleen McKeown explores natural language text and presents a formal analysis of problems in a computer program, TEXT. |
| confident adaptive language modeling: UML Distilled Martin Fowler, 2018-08-30 More than 300,000 developers have benefited from past editions of UML Distilled . This third edition is the best resource for quick, no-nonsense insights into understanding and using UML 2.0 and prior versions of the UML. Some readers will want to quickly get up to speed with the UML 2.0 and learn the essentials of the UML. Others will use this book as a handy, quick reference to the most common parts of the UML. The author delivers on both of these promises in a short, concise, and focused presentation. This book describes all the major UML diagram types, what they're used for, and the basic notation involved in creating and deciphering them. These diagrams include class, sequence, object, package, deployment, use case, state machine, activity, communication, composite structure, component, interaction overview, and timing diagrams. The examples are clear and the explanations cut to the fundamental design logic. Includes a quick reference to the most useful parts of the UML notation and a useful summary of diagram types that were added to the UML 2.0. If you are like most developers, you don't have time to keep up with all the new innovations in software engineering. This new edition of Fowler's classic work gets you acquainted with some of the best thinking about efficient object-oriented software design using the UML--in a convenient format that will be essential to anyone who designs software professionally. |
| confident adaptive language modeling: Cbt Fundamentals: Theory And Cases Skinner, Vanessa, Wrycraft, Nick, 2014-10-01 CBT Fundamentals is an indispensable, introductory guide for all mental health practitioners embarking on CBT training. |
| confident adaptive language modeling: Applied Predictive Modeling Max Kuhn, Kjell Johnson, 2013-05-17 Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. |
| confident adaptive language modeling: Understanding by Design Grant P. Wiggins, Jay McTighe, 2005 What is understanding and how does it differ from knowledge? How can we determine the big ideas worth understanding? Why is understanding an important teaching goal, and how do we know when students have attained it? How can we create a rigorous and engaging curriculum that focuses on understanding and leads to improved student performance in today's high-stakes, standards-based environment? Authors Grant Wiggins and Jay McTighe answer these and many other questions in this second edition of Understanding by Design. Drawing on feedback from thousands of educators around the world who have used the UbD framework since its introduction in 1998, the authors have greatly revised and expanded their original work to guide educators across the K-16 spectrum in the design of curriculum, assessment, and instruction. With an improved UbD Template at its core, the book explains the rationale of backward design and explores in greater depth the meaning of such key ideas as essential questions and transfer tasks. Readers will learn why the familiar coverage- and activity-based approaches to curriculum design fall short, and how a focus on the six facets of understanding can enrich student learning. With an expanded array of practical strategies, tools, and examples from all subject areas, the book demonstrates how the research-based principles of Understanding by Design apply to district frameworks as well as to individual units of curriculum. Combining provocative ideas, thoughtful analysis, and tested approaches, this new edition of Understanding by Design offers teacher-designers a clear path to the creation of curriculum that ensures better learning and a more stimulating experience for students and teachers alike. |
| confident adaptive language modeling: Swaiman's Pediatric Neurology - E-Book Kenneth F. Swaiman, Stephen Ashwal, Donna M Ferriero, Nina F Schor, 2011-11-11 Swaiman’s Pediatric Neurology, by Drs. Kenneth Swaiman, Stephen Ashwal, Donna Ferriero, and Nina Schor, is a trusted resource in clinical pediatric neurology with comprehensive, authoritative, and clearly-written guidance. Extensively updated to reflect advancements in the field, this fifth edition covers new imaging modalities such as pediatric neuroimaging, spinal fluid examination, neurophysiology, as well as the treatment and management of epilepsy, ADHD, infections of the nervous system, and more. The fully searchable text is now available online at www.expertconsult.com, along with downloadable images and procedural videos demonstrating intraventricular hemorrhage and white matter injury, making this an indispensable multimedia resource in pediatric neurology. Gain a clear visual understanding from the numerous illustrations, informative line drawings, and summary tables. Tap into the expertise of an authoritative and respected team of editors and contributors. Get comprehensive coverage of all aspects of pediatric neurology with a clinical focus useful for both the experienced clinician and the physician-in-training. Access the fully searchable text online at www.expertconsult.com, along with 16 additional online-only chapters, downloadable images, videos demonstrating intraventricular hemorrhage and white matter injury, and links to PubMed. Stay current on recent developments through extensive revisions: a new chapter on paraneoplastic syndromes in children; a new section on congenital brain malformations written by leading international authorities; and another one on cutting-edge pediatric neuroscience concepts relating to plasticity, neurodegeneration of the developing brain, and neuroinflammation. Apply the latest information on diagnostic modalities, including pediatric neuroimaging, spinal fluid examination, and neurophysiology |
| confident adaptive language modeling: Leveraging Applications of Formal Methods, Verification and Validation. Technologies for Mastering Change Tiziana Margaria, Bernhard Steffen, 2014-09-26 The two-volume set LNCS 8802 and LNCS 8803 constitutes the refereed proceedings of the 6th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2014, held in Imperial, Corfu, Greece, in October 2014. The total of 67 full papers was carefully reviewed and selected for inclusion in the proceedings. Featuring a track introduction to each section, the papers are organized in topical sections named: evolving critical systems; rigorous engineering of autonomic ensembles; automata learning; formal methods and analysis in software product line engineering; model-based code generators and compilers; engineering virtualized systems; statistical model checking; risk-based testing; medical cyber-physical systems; scientific workflows; evaluation and reproducibility of program analysis; processes and data integration in the networked healthcare; semantic heterogeneity in the formal development of complex systems. In addition, part I contains a tutorial on automata learning in practice; as well as the preliminary manifesto to the LNCS Transactions on the Foundations for Mastering Change with several position papers. Part II contains information on the industrial track and the doctoral symposium and poster session. |
| confident adaptive language modeling: Precision medicine approaches for heterogeneous conditions such as autism spectrum disorders (The need for a biomarker exploration phase in clinical trials - Phase 2m) David Quentin Beversdorf, Craig Andrew Erickson, Paul Wang, Thomas Frazier, 2023-04-17 Many therapeutic interventions for autism spectrum disorder fail when they are examined in a clinical trial. Frequently, there is a subset of patients that responds very well to the intervention, while others do not, and the overall result does not yield a positive result. As autism spectrum disorder is highly heterogeneous in its underlying genetics and other etiological risk factors, as well as its heterogeneous phenotypic manifestation, this variability in response to any specific treatment is not entirely surprising. However, it remains a challenge to meaningfully subtype this heterogeneity for targeted treatment. The purpose of this research topic is to solicit articles that address the heterogeneity in autism spectrum disorder in a manner that may meaningfully contribute to targeted treatment approaches. Studies that address the heterogeneity of autism that could theoretically lead to targeted treatment, and studies that more directly address the use of a marker in association with response to a treatment, are both aspects that will contribute to this purpose. It is hoped that this Research Topic will yield articles that can help advance the field towards precision medicine in autism spectrum disorders. Manuscripts that contribute to the specification of the heterogeneity of autism spectrum disorder in a manner that could theoretically lead to targeted treatment would be appropriate for this research topic. Additionally, articles that utilize subtyping in relation to response to treatment would be appropriate for this research topic. |
| confident adaptive language modeling: Surfing Uncertainty Andy Clark, 2016 Exciting new theories in neuroscience, psychology, and artificial intelligence are revealing minds like ours as predictive minds, forever trying to guess the incoming streams of sensory stimulation before they arrive. In this up-to-the-minute treatment, philosopher and cognitive scientist Andy Clark explores new ways of thinking about perception, action, and the embodied mind. |
| confident adaptive language modeling: Advanced Data Mining and Applications Bohan Li, Lin Yue, Jing Jiang, Weitong Chen, Xue Li, Guodong Long, Fei Fang, Han Yu, 2022-01-31 This book constitutes the proceedings of the 17th International Conference on Advanced Data Mining and Applications, ADMA 2021, held in Sydney, Australia in February 2022.* The 26 full papers presented together with 35 short papers were carefully reviewed and selected from 116 submissions. The papers were organized in topical sections in Part I, including: Healthcare, Education, Web Application and On-device application. * The conference was originally planned for December 2021, but was postponed to 2022. |
| confident adaptive language modeling: Advances in Knowledge Discovery and Data Mining De-Nian Yang, |
| confident adaptive language modeling: Soft Computing and Intelligent Systems Madan M. Gupta, 1999-10-28 The field of soft computing is emerging from the cutting edge research over the last ten years devoted to fuzzy engineering and genetic algorithms. The subject is being called soft computing and computational intelligence. With acceptance of the research fundamentals in these important areas, the field is expanding into direct applications through engineering and systems science.This book cover the fundamentals of this emerging filed, as well as direct applications and case studies. There is a need for practicing engineers, computer scientists, and system scientists to directly apply fuzzy engineering into a wide array of devices and systems. |
| confident adaptive language modeling: Psychology of Learning and Motivation , 2017-01-23 Psychology of Learning and Motivation, Volume 66, the latest release in this longstanding series publishes empirical and theoretical contributions in cognitive and experimental psychology, ranging from classical and instrumental conditioning, to complex learning and problem-solving. Each chapter thoughtfully integrates the writings of leading contributors who present and discuss significant bodies of research relevant to their discipline. Volume 66 includes chapters on such varied topics as prospective memory, metacognitive information processing, basic memory processes during reading, working memory capacity, attention, perception and memory, short-term memory, language processing, and causal reasoning. - Presents the latest information in the highly regarded Psychology of Learning and Motivation series - Provides an essential reference for researchers and academics in cognitive science - Contains information relevant to both applied concerns and basic research |
| confident adaptive language modeling: Model-Driven Software Engineering in Practice Marco Brambilla, Jordi Cabot, Manuel Wimmer, 2012-09-24 This book discusses how model-based approaches can improve the daily practice of software professionals. This is known as Model-Driven Software Engineering (MDSE) or, simply, Model-Driven Engineering (MDE). MDSE practices have proved to increase efficiency and effectiveness in software development, as demonstrated by various quantitative and qualitative studies. MDSE adoption in the software industry is foreseen to grow exponentially in the near future, e.g., due to the convergence of software development and business analysis. The aim of this book is to provide you with an agile and flexible tool to introduce you to the MDSE world, thus allowing you to quickly understand its basic principles and techniques and to choose the right set of MDSE instruments for your needs so that you can start to benefit from MDSE right away. The book is organized into two main parts. The first part discusses the foundations of MDSE in terms of basic concepts (i.e., models and transformations), driving principles, application scenarios and current standards, like the well-known MDA initiative proposed by OMG (Object Management Group) as well as the practices on how to integrate MDSE in existing development processes. The second part deals with the technical aspects of MDSE, spanning from the basics on when and how to build a domain-specific modeling language, to the description of Model-to-Text and Model-to-Model transformations, and the tools that support the management of MDSE projects. The book is targeted to a diverse set of readers, spanning: professionals, CTOs, CIOs, and team managers that need to have a bird's eye vision on the matter, so as to take the appropriate decisions when it comes to choosing the best development techniques for their company or team; software analysts, developers, or designers that expect to use MDSE for improving everyday work productivity, either by applying the basic modeling techniques and notations or by defining new domain-specific modeling languages and applying end-to-end MDSE practices in the software factory; and academic teachers and students to address undergrad and postgrad courses on MDSE. In addition to the contents of the book, more resources are provided on the book's website, including the examples presented in the book. Table of Contents: Introduction / MDSE Principles / MDSE Use Cases / Model-Driven Architecture (MDA) / Integration of MDSE in your Development Process / Modeling Languages at a Glance / Developing your Own Modeling Language / Model-to-Model Transformations / Model-to-Text Transformations / Managing Models / Summary |
| confident adaptive language modeling: A Practical Guide for Medical Teachers, E-Book John Dent, Ronald M. Harden, Dan Hunt, 2021-04-24 Highly regarded in the field of medical education, A Practical Guide for Medical Teachers provides accessible, highly readable, and practical information for those involved in basic science and clinical medicine teaching. The fully updated 6th Edition offers valuable insights into today's medical education. Input from global contributors who offer an international perspective and multi-professional approach to topics of interest to all healthcare teachers. With an emphasis on the importance of developing educational skills in the delivery of enthusiastic and effective teaching, it is an essential guide to maximizing teaching performance. - Offers comprehensive, succinct coverage of curriculum planning and development, assessment, student engagement, and more. - Includes 10 new chapters that discuss the international dimension to medical education, clinical reasoning, the roles of teachers, mentoring, burnout and stress, the patient as educator, professional identity, curriculum and teacher evaluation, how students learn, and diversity, equality and individuality. - Delivers the knowledge and expertise of more than 40 international contributors. - Features helpful boxes highlighting practical tips, quotes, and trends in today's medical education. |
CONFIDENT Definition & Meaning - Merriam-Webster
The meaning of CONFIDENT is full of conviction : certain. How to use confident in a sentence. Is it confident or confidant? (Or is it confidante?)
CONFIDENT | English meaning - Cambridge Dictionary
CONFIDENT definition: 1. being certain of your abilities or having trust in people, plans, or the future: 2. being…. Learn more.
CONFIDENT Definition & Meaning - Dictionary.com
Confident definition: having strong belief or full assurance; sure.. See examples of CONFIDENT used in a sentence.
Confident - definition of confident by The Free Dictionary
confident - having or marked by confidence or assurance; "a confident speaker"; "a confident reply"; "his manner is more confident these days"; "confident of fulfillment"
CONFIDENT definition in American English | Collins English …
If a person or their manner is confident, they feel sure about their own abilities, qualities, or ideas.
What does confident mean? - Definitions.net
Confident is an adjective that describes a person who believes in their abilities and has a strong belief in themselves. It often refers to someone who is assured, self-assured, and possesses a …
confident adjective - Definition, pictures, pronunciation and usage ...
confident completely sure that something will happen in the way that you want or expect: I'm confident that you'll get the job. The team is confident that they will win. Confident is a stronger …
Confident vs. Confidence — What’s the Difference?
Oct 17, 2023 · When someone is "Confident", it means they display a strong sense of self-belief and assurance. "Confidence", however, refers to the internal feeling or trust in one's own …
Confidant vs. Confident: What's the Difference? - Grammarly
While confidant and confident sound alike, their meanings are distinct. A confidant is someone you trust with your secrets, serving a noun in the English language. In contrast, confident …
CONFIDENT Synonyms: 105 Similar and Opposite Words - Merriam-Webster
Synonyms for CONFIDENT: assured, optimistic, hopeful, secure, self-confident, proud, self-assured, smug; Antonyms of CONFIDENT: insecure, timid, diffident, meek, nervous, humble, …
CONFIDENT Definition & Meaning - Merriam-Webster
The meaning of CONFIDENT is full of conviction : certain. How to use confident in a sentence. Is it confident or confidant? (Or is it confidante?)
CONFIDENT | English meaning - Cambridge Dictionary
CONFIDENT definition: 1. being certain of your abilities or having trust in people, plans, or the future: 2. being…. Learn more.
CONFIDENT Definition & Meaning - Dictionary.com
Confident definition: having strong belief or full assurance; sure.. See examples of CONFIDENT used in a sentence.
Confident - definition of confident by The Free Dictionary
confident - having or marked by confidence or assurance; "a confident speaker"; "a confident reply"; "his manner is more confident these days"; "confident of fulfillment"
CONFIDENT definition in American English | Collins English …
If a person or their manner is confident, they feel sure about their own abilities, qualities, or ideas.
What does confident mean? - Definitions.net
Confident is an adjective that describes a person who believes in their abilities and has a strong belief in themselves. It often refers to someone who is assured, self-assured, and possesses a …
confident adjective - Definition, pictures, pronunciation and usage ...
confident completely sure that something will happen in the way that you want or expect: I'm confident that you'll get the job. The team is confident that they will win. Confident is a stronger …
Confident vs. Confidence — What’s the Difference?
Oct 17, 2023 · When someone is "Confident", it means they display a strong sense of self-belief and assurance. "Confidence", however, refers to the internal feeling or trust in one's own …
Confidant vs. Confident: What's the Difference? - Grammarly
While confidant and confident sound alike, their meanings are distinct. A confidant is someone you trust with your secrets, serving a noun in the English language. In contrast, confident …
CONFIDENT Synonyms: 105 Similar and Opposite Words - Merriam-Webster
Synonyms for CONFIDENT: assured, optimistic, hopeful, secure, self-confident, proud, self-assured, smug; Antonyms of CONFIDENT: insecure, timid, diffident, meek, nervous, humble, …
