Application of statistical pattern recognition and deep learning for morphological classification in radio astronomy by Becker, Adolf Burger

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Factors affecting irrigation management decision-making : the case of Taung Irrigation Scheme in North West Province of South Africa

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Unethical decision making : towards understanding the factors that influence a white collar criminal’s decision to commit a crime

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A Machine Learning Approach to Predicting the Employability of a Graduate by Modibane, Masego

“…The aim for the dissertation is to build a machine learning classification model that can predict a students likelihood to become employed, based on their student data (for example, their GPA, degree/s held etc). …”
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Automated Machine Learning for Predicting Trends in Time Series Data by Kouassi, Kouame

“…However, manual ASHO is expensive and often results in a sub-optimal or mediocre model because it needs extensive experimentation as well as domain specific and Machine Learning (ML) expert knowledge. …”
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Forecasting energy consumption on mines using machine learning techniques by Esterhuizen, Lohani

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Basic educational reform and provision of quality education in South Africa (1994-2018): A tentative exploration of policy in the making by Lawrence, Audrey Rozanne

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Predictive Maintenance in Rail Transportation: An Explainable Machine Learning Approach by Mabaso, Nelisa Zamantungwa Sphumelele

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Non-linear neurocontrol of chemical processes using reinforcement learning by Hunter, Stephen Leon

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Neurocontroller development for nonlinear processes utilising evolutionary reinforcement learning by Conradie, Alex van Eck

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Direct and indirect multimodal few-shot learning of speech and images by Nortje, Leanne

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The Process of Transformative Learning in Executive Coaching : a Realist Evaluation

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Education leadership learning : the experiences and perceptions of MEder's degree students

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Effecting organisation change in Eskom by creating a learning environment

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The design and use of an outdoor learning environment for sensory and motor stimulation

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Predicting household poverty with machine learning methods: the case of Malawi by Chinyama, Francis

“…Area under the Curve, Receiver Operating Characteristic curve, recall, precision, F1 score, Matthews Correlation Coefficient and Cohen's Kappa scores confirmed the classification models' reliability. The study, therefore, established that poverty can be predicted by open-source machine learning algorithms using a substantially reduced number of features with accuracy comparable to using the full feature set. …”
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The use of a Virtual Learning Environment (VLE) to embed library information services in a Blended Learning Environment (BLE) : a University of Pretoria Engineering study

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Explaining "non-reform" in special needs education policy in South Africa

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Online prognostic strategies with deep leaning models for fleets of engineering assets

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