Predicting the Next Word with Machine Learning model

dc.contributor.authorHala ,Mohamed Islam
dc.contributor.authorHibi, Adam
dc.contributor.authorKaddour, Rabeh
dc.date.accessioned2026-01-25T08:22:18Z
dc.date.issued2026
dc.descriptionGraduation thesis, third year, Bachelor of Computer Science
dc.description.abstractNext Word Prediction is a task within Natural Language Processing (NLP) that involves predicting the next word in a given sequence based on the preceding words. This process is crucial for a wide range of applications, including text completion, machine translation, and intelligent writing assistants. By analyzing large amounts of textual data, machine learning models can identify patterns in language use and generate contextually relevant predictions. The goal of this report is to explore the implementation of next-word prediction using deep learning models, particularly Recurrent Neural Networks (RNNs) and Transformers, which have shown significant improvements in prediction accuracy over traditional methods.
dc.identifier.citationHala ,Mohamed Islam. Hibi, Adam . Kaddour, Rabeh. Predicting the Next Word with Machine Learning model .University of El Oued, Faculty of Exact Sciences, Department of Computer Science, 2025
dc.identifier.urihttps://archives.univ-eloued.dz/handle/123456789/41080
dc.language.isoen
dc.publisherUniversité of Eloued جامعة الوادي
dc.subjectNext Word Prediction
dc.subjectNatural Language Processing
dc.subjectDeep Learning
dc.subjectRecurrent Neural Networks
dc.subjectTransformers
dc.titlePredicting the Next Word with Machine Learning model
dc.typeThesis

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