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Djellab A. AI, Data Science and Machine Learning Platforms

My name is Djellab A. and I have over 3 years of experience in the tech industry. I specialize in the following technologies: TensorFlow, Data Science, Anomaly Detection, Reinforcement Learning, Python, etc.. I hold a degree in Master's degree. Some of the notable projects I've worked on include: Chatbot-Symptom-Checker-Powered-by-AI-and-LLM, FaceShapeClassifier – AI-Powered Face Shape Detection, RubikCubeColorExtractor. I am based in Montreal, Canada. I've successfully completed 3 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.

Main technologies

  • AI, Data Science and Machine Learning Platforms

    3 years

  • TensorFlow

    2 Years

  • Data Science

    1 Year

  • Anomaly Detection

    1 Year

Additional skills

Direct hire

Potentially possible

Previous Company

Sonelgaz

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Experience Highlights

Chatbot-Symptom-Checker-Powered-by-AI-and-LLM

This AI-driven medical chatbot leverages LLMs, NLP, and machine learning to enhance diagnostic accuracy and treatment guidance. It features symptom extraction, medical term translation, and disease pr

FaceShapeClassifier – AI-Powered Face Shape Detection

FaceShapeClassifier is an AI-powered deep learning model for automatic face shape recognition. It classifies faces into oval, round, square, heart, and diamond shapes using CNNs, facial landmark detec

RubikCubeColorExtractor

This project utilizes a YOLO-based computer vision model to detect and extract colors from a Rubik’s Cube with high accuracy. The model processes images to identify individual colored squares, enablin

Education

  • Higher school of computer science

    Master's degree in Artificial Intelligence and Data Science

    2018-01-01-2024-01-01

Languages

  • Arabic (Native or Bilingual)
  • English (Fluent)✓
  • French (Fluent)