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

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

Subjects: “…Learning Management System…”
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Factors influencing success in adult learning on learnerships

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Social entrepreneurs’ conceptions of incubator-based learning

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Deep adaptive anomaly detection using an active learning framework by Sekyi, Emmanuel

“…This work seeks to answer the question, can we deform these features so as to make the anomalies standout and hence improve the anomaly detection outcome? We employ a Deep Learning and an Active Learning framework to learn features for anomaly detection. …”
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Determining the nature of free will using machine learning by Hall, Siobhan

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The contextual nature of learning in community schools in Lusaka

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Secondary school teachers’ experiences of learning support by Hannah, Julia Elizabeth

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Machine learning for antenna array failure analysis by De Lange, Lydia

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