University Admission Prediction Using Google Vertex AI

Katti, Jayashree; Agarwal, Jony; Bharata, Swapnil; Shinde, Swati; Mane, Saral; Biradar, Vinod

doi:10.1109/icaitpr51569.2022.9844176

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2023

2024

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Cited by 7 publications

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“…Recent Advances and Future Directions: Highlight recent advances in the field, such as the integration of deep learning techniques, natural language processing for analysing personal statements, and the use of advanced optimization algorithms. Propose potential avenues for future research to address current limitations and improve model performance [5]. Conclusion: Summarize key findings from the literature review and emphasize the significance of developing accurate and transparent admission prediction models for enhancing the university admissions process [1].…”

Section: Literature Surveymentioning

confidence: 99%

Forecasting Futures: Predicting University Admissions with Machine Learning

Bansode

2024

IJSREM

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The process of university admissions is inherently complex, often relying on various factors such as academic records, standardized test scores, extracurricular activities, recommendation letters, and personal statements. In recent years, machine learning (ML) techniques have shown promising results in predicting admission outcomes, aiding both prospective students and admissions committees in decision-making processes. Keywords: University admission, Machine learning, Predictive modelling, Classification, Regression, Data pre-processing.

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Section: Literature Surveymentioning

confidence: 99%