mohammed amine

Developed real-time gesture recognition and facial emotion detection systems using OpenCV and deep learning models (CNNs, PyTorch). Built a facial emotion detection system using deep learning Applied CNNs for voice recognition and speech transcription Designed NLP pipelines using BERT & LSTM for sentiment analysis Applied object detection and tracking techniques for realtime video analysis.

Automated candidate trading workflows (5-step cohort pipeline) using Make and n8n. Integrated Pipefy with AI-driven email workflows, sending personalized responses with attached PDFs. Developed automation to extract structured data from Gmail and store it in Excel for reporting. Leveraged LLMs to generate captions and automate social media posting, enhancing engagement.

Built a PC intervention management system to optimize technician productivity Focused on accurate service tracking and real-time reporting Relevance: Project management, system monitoring, and desktop software skills valuable for building cybermonitoring tools.