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Schedule Interview NowMy name is Ahmed G. and I have over 1 year of experience in the tech industry. I specialize in the following technologies: Machine Learning, Artificial Intelligence, TensorFlow, PyTorch, Computer Vision, etc.. I hold a degree in Bachelor of Engineering (BEng). Some of the notable projects I've worked on include: YouTube Video Transcription & Q/A Tool, Arabic RAG for Egyptian Tax Law, AI-Powered Multi-Task Chat Assistant (Translation, Summarization, Q&A), license-plate-detection-ocr, SRGAN, etc.. I am based in Al Mahallah al Kubra, Egypt. I've successfully completed 7 projects while developing at Softaims.
I thrive on project diversity, possessing the adaptability to seamlessly transition between different technical stacks, industries, and team structures. This wide-ranging experience allows me to bring unique perspectives and proven solutions from one domain to another, significantly enhancing the problem-solving process.
I quickly become proficient in new technologies as required, focusing on delivering immediate, high-quality value. At Softaims, I leverage this adaptability to ensure project continuity and success, regardless of the evolving technical landscape.
My work philosophy centers on being a resilient and resourceful team member. I prioritize finding pragmatic, scalable solutions that not only meet the current needs but also provide a flexible foundation for future development and changes.
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smart badya
A full-stack AI-powered application to extract, transcribe, and analyze YouTube video content. This tool intelligently handles subtitles or audio transcription and can generate challenging, compound q
Developed an Arabic Retrieval-Augmented Generation (RAG) chatbot to answer questions about Egyptian tax law. It uses OCR to extract text from legal PDFs, stores data in a Chroma vector database with m
Developed an AI-powered assistant using LangChain, Streamlit, and Groq’s LLaMA3 model that classifies user input and performs translation, summarization, or general Q&A. It uses a classification chain
The main objective of this project is to provide an automated system for detecting vehicle license plates and extracting their corresponding text using deep learning and optical character recognition
Developed and implemented SRGAN (Super-Resolution Generative Adversarial Network) to enhance image resolution with deep learning techniques, including model training, optimization, and detailed visual
Bachelor of Engineering (BEng) in Computer engineering
2018-01-01-2023-01-01