metaai ilhem Yahiaoui hadjerYahiaoui hadjer2025-11-132025MM/929https://dspace.univ-bba.dz/handle/123456789/1027In recent years, the field of machine translation has seen a remarkable development thanks to the rapid advancement of artificial intelligence (AI) technologies, especially with the emergence of deep learning-based Transformers models. These models have contribu ted to improving translation quality, especially when it comes to languages that are not standardized or lack sufficient linguistic resources, such as Algerian Darija. This study aims to build and evaluate a deep learning-based machine translation mo del for translating texts from Algerian Darija to English. To achieve this goal, a dataset containing sentences written in Algerian Darija and their corresponding English trans lations was collected and processed, and a model based on the Transformer architecture was trained using this data.frMachine TranslationArtificial IntelligenceDeep LearningTransformer Mo- delsHuman TranslationTraditional TranslationAdaptersStandard ArabicAlge rian DarijaMultilingual DatasetLinguistic FeaturesNeural TranslationThesis