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Didactic strategies --- leerdoelen --- feedback --- leren

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Leer hoe u feedback geeft en ontvangt in slechts 50 minuten met dit praktische en beknopte boek. Feedback is een integraal onderdeel van de meeste moderne werkomgevingen, en dient een belangrijk doel bij prestatiebeoordeling en professionele ontwikkeling. Als feedback echter niet constructief is, kan het de motivatie ondermijnen en wrok in de hand werken. Daarom is het van vitaal belang dat u lof en kritiek op een doeltreffende manier leert geven als u het beste wilt halen uit de mensen om u heen. In dit boek leert u hoe constructieve feedback nuttig kan zijn bij teammanagement, professionele relaties en persoonlijke ontwikkeling. Het bevat ook nuttig advies over wanneer en hoe u feedback geeft en tips over het accepteren van feedback van anderen, zodat u optimaal gebruik kunt maken van deze waardevolle kans om uw prestaties te verbeteren.

Didactics --- Mass communications --- communicatie --- communicatiemanagement --- feedback --- communicatietheorieën --- communicatiewetenschappen

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Unlock the full potential of reinforcement learning (RL), a crucial subfield of Artificial Intelligence, with this comprehensive guide. This book provides a deep dive into RL's core concepts, mathematics, and practical algorithms, helping you to develop a thorough understanding of this cutting-edge technology. Beginning with an overview of fundamental concepts such as Markov decision processes, dynamic programming, Monte Carlo methods, and temporal difference learning, this book uses clear and concise examples to explain the basics of RL theory. The following section covers value function approximation, a critical technique in RL, and explores various policy approximations such as policy gradient methods and advanced algorithms like Proximal Policy Optimization (PPO). This book also delves into advanced topics, including distributed reinforcement learning, curiosity-driven exploration, and the famous AlphaZero algorithm, providing readers with a detailed account of these cutting-edge techniques. With a focus on explaining algorithms and the intuition behind them, The Art of Reinforcement Learning includes practical source code examples that you can use to implement RL algorithms. Upon completing this book, you will have a deep understanding of the concepts, mathematics, and algorithms behind reinforcement learning, making it an essential resource for AI practitioners, researchers, and students. You will: Grasp fundamental concepts and distinguishing features of reinforcement learning, including how it differs from other AI and non-interactive machine learning approaches Model problems as Markov decision processes, and how to evaluate and optimize policies using dynamic programming, Monte Carlo methods, and temporal difference learning Utilize techniques for approximating value functions and policies, including linear and nonlinear value function approximation and policy gradient methods Understand the architecture and advantages of distributed reinforcement learning Master the concept of curiosity-driven exploration and how it can be leveraged to improve reinforcement learning agents Explore the AlphaZero algorithm and how it was able to beat professional Go players.

Reinforcement learning. --- Feedback control systems. --- Python (Computer program language)

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'From Assessment to Feedback' addresses the need for practical and enriching literature on assessment and feedback in language teaching and learning. De Florio documents research-based forms of assessment and feedback in a succinct and accessible way, as the basis for classroom-oriented procedures in foreign/second language teaching.

English language --- Feedback (Psychology) --- Study and teaching --- Foreign speakers. --- Learning, Psychology of --- Reinforcement (Psychology) --- Germanic languages

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Employees --- Learning --- Feedback (Psychology) --- Communication in personnel management --- Training of --- Coaching of