Analysis of Machine Learning Algorithms for Time Series Prediction by Naidoo, Kimendree

“…This research investigates and evaluates machine learning algorithms that can be used for time series prediction. …”
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Reinforcement learning microservices scheduler in intelligent edge computing

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The application of machine learning for computational electromagnetic solver selection by De la Bat, Willem

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A machine learning framework for security forecasting and trading by Van Schalkwyk, Philip

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Autonomous racing on unseen tracks using reinforcement learning by Jefferies, Devin Wayne Patrick

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The role of organisational behaviour in establishing a corporate academy in the construction industry

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Students' experiences of WebCT

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An evaluation of the feasibility of using Moodle to develop an online learning program for the Grade 12 Literature component of the First Additional Language syllabus in South Afri... by Van Rooyen, Marinda

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Latent semantic models : a study of probabilistic models for text in information retrieval

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Multilingual preschool learners: a collaborative approach to communication intervention

Subjects: “…Service delivery model…”
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Application of statistical pattern recognition and deep learning for morphological classification in radio astronomy by Becker, Adolf Burger

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Die onderrigleervoorkeure van Generasie Z-studente in hoër onderwys : ʼn bestek-oorsig by Van der Merwe, Mareli Winter

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Forecasting energy consumption on mines using machine learning techniques by Esterhuizen, Lohani

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

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Unravelling black box machine learning methods using biplots by Rowan, Adriaan

“…This allows the output of the model to be represented by colour coding each point on the biplot plane according to the output of an independently calibrated machine learning model. …”
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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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Machine Learning Multimodal Framework for Fake News Detection and Mitigation by GabAllah, Nada A

“…Specifically, it will examine how contextual information can enhance detection of fake social posts and the extent to which integrating news articles can further enhance this performance. Large langugae models are used for textual representation of social posts and news articles, and deep learning neural networks are used to capture the contextual features of the text and identify the post as fake or real. …”
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Radar-Based Multi-Target Classification Using Deep Learning by Mashanda, Nyasha Ernest

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Extractive Text Summarization on Single Documents Using Deep Learning by Mohamed, Shehab Mostafa Abdel-Salam

“…The objective of this thesis is to study the performance of deep learning-based models on text summarization through a series of experiments, and propose “SqueezeBERTSum”, a trained summarization model fine-tuned with the SqueezeBERT encoder which achieved competitive ROUGE scores retaining original BERT model’s performance by 98% with ~49% fewer trainable parameters.…”
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