Siham Bouguern

Siham Bouguern develops AI and machine learning solutions from her base in France, specializing in applications for environmental sustainability, healthcare systems, and industrial automation. Her technical portfolio centers on Natural Language Processing implementations, including Neural Machine Translation systems and YOLOv8-based computer vision projects. She documents her work through open-source repositories on GitHub, primarily utilizing Python and established deep learning frameworks. Her Substack publication analyzes the deployment of Large Language Models, Generative AI, and machine learning systems across critical sectors. The technical writing covers Industrial IoT architecture, predictive maintenance algorithms, and supply chain optimization methods. Her coverage emphasizes the measurable impacts of AI implementation in manufacturing environments. Bouguern's engineering work combines industrial IoT sensor integration, Industry 4.0 digital transformation frameworks, and smart manufacturing systems. She develops predictive maintenance solutions using machine learning models, implements computer vision for quality control, and designs AI-driven optimization tools for manufacturing processes. Her technical focus includes documenting reproducible methods for integrating AI systems within existing industrial infrastructure.