Machine learning model based analysis of land use land cover change and assessing its potential impact on surface runoff in meki watershed, rift valley lakes basin, Ethiopia

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Trends, problems, and solutions in causality and reinforcement learning by Grimbly, St John

“…Although relevant in both model-based and model-free scenarios, focus is placed on model-based modalities where one can view the various models as being causal models. …”
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Evaluating transformers as memory systems in reinforcement learning by Makkink, Thomas

“…Early research into transformers as memory mechanisms for reinforcement learning indicated that the canonical model is not suitable, and that additional gated recurrent units and architectural modifications are necessary to stabilize these models. …”
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Barriers to learning mathematics in rural secondary schools by Sao, Lawrence Y. T.

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Predicting mergers and acquisitions using machine learning by Beckenstrater, Gordon

“…The findings are that all the advanced algorithms surpassed the performance of logistic regression in M&A prediction, signalling a shift from traditional statistical methods to advanced machine learning techniques. LightGBM and the Ensemble model displayed the best performance in M&A prediction. …”
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Reinforcement learning for the control of traffic flow on highways by Schmidt-Dumont, Thorsten

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Grade 9 learners' opportunity to learn algebra

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Learning from failure in the context of business rescue

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Influencer Wisdom As A Conceptual Model To Understand Influencer Strategies, Tactics, And Success by Asaad, Mariam Ashraf

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Representation learning for regime detection in financial markets by Orton, Alexa

“…Market phase detection for each model is carried out using three data configurations: i.) …”
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Small-scale distributed machine learning in R by Taylor, Brenden

“…Machine learning models generally require large amounts of data to train and thus are computationally expensive, both in the absolute sense of actual compute time, and in the relative sense of the numerical complexity of the underlying calculations. …”
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Mixed-Criticality Scheduling Using Reinforcement Learning by ElSeadawy, Omar

“…We propose a somewhat unconventional approach, where we tackle the modeling complexities using deep reinforcement learning, particularly suitable for problems that generate a sequence of decisions in dynamic environments. …”
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Optimizing learning & teaching on paediatric ward rounds by Mantzor, Savarra

“…Based on the findings from this study, a structured bedside teaching model, specifically SNAPPS, offers a holistic approach to maximize learning and teaching, addressing several learner and environmental needs concurrently. …”
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Applying the Seven Principles of Learning to Development Communication by Abd El Ghaffar, Lina

“…The suggested paradigm is more audience-centric than the current dominant paradigm and more structured than the current participatory paradigm. The suggested learning paradigm builds its conceptual model around the development communication campaign audience’s internal and external factors that directly influence their decision making. …”
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Computational Psychiatry - Neuropsychological Bayesian reinforcement learning by Wolpe, Zach

“…We were able to successfully predict the subjects' behaviour in this task by fitting a Bayesian Reinforcement Learning model, alluding to the mechanics of the latent biological decision generating process and executive functions. …”
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Multimodal one-shot learning of speech and images by Eloff, Ryan

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The multiplicative reasoning proficiency of learners with learning difficulties

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Factors influencing success in adult learning on learnerships

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Die gebruik van ’n leerbestuurstelsel in die ontwerp van kentekeninhoud vir ’n jeugbeweging

Subjects: “…Learning Management System…”
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Medicine and medical process as a learning system by Van Wyk, Gerrit Christian Burggraf

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