Chergui, AbdeNnourBoutchicha, Houssam EddineSupervisor: Gadri, Said2023-07-102023-07-102023-06-10https://repository.univ-msila.dz/handle/123456789/40248This graduation project aims to address plant disease issues and promote crop yields in the context of the global agricultural revolution. It is suggested to use deep learning and machine learning techniques to address these challenges. Initially, we used a DL model to automate the detection of plant diseases. The next phase of the project focuses on improving crop yields by leveraging ML algorithms, this project emphasizes the role of integrating advanced technologies such as DL and ML in solving agricultural obstacles.enSmart Farming,Machine Learning,Deep LearningThesis