Mohamed Hamidi

Analysis of data from an educational system and scoring. Design of a public health application. Data cleaning. Statistical analyses to justify the idea. Anticipation of building consumption needs. Supervised learning. Segmentation of e-commerce site customers. Unsupervised learning. Classification of consumer goods. Natural language processing. Image processing. Deep learning. Implementation of a scoring model. Deployment of the model on an API. Code tracking via MLFlow. Development of a dashboard. Deployment of a model on the cloud. Setting up a Big Data environment (via AWS). Parallelization of calculations (via PySpark).

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Centralization and cleaning of data in the UNIK tool, with in-depth analysis (Python). Modeling of datasets using the KNN algorithm to identify similar projects. Design and deployment of an interactive and comparative Dashboard (Streamlit): Integration of analytical visuals, linear regression, confidence band, and dynamic filters. Development of a project feasibility indicator. Option to download summaries in PowerPoint directly from the dashboard.