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OmarFaig/README.md

💫 About Me

🚀 What I'm Currently Working On

  • C# .NET Development: Building a cross-platform weather application using C# with .NET and Avalonia UI, aiming for a seamless experience across devices.
  • Software Engineering: Continuously improving my skills in developing efficient, user-friendly applications and refining workflows with modern development practices.
  • MLOps & Automation: Working on streamlining machine learning workflows and optimizing deployment pipelines for production-ready AI solutions.
  • Computer Vision & AI: Experimenting with image recognition models, object detection, and custom transformer models in NLP to enhance understanding of advanced ML concepts.

🌱 Currently Learning

  • Edge Computing: Exploring techniques to deploy AI models on low-power devices for real-time processing and integration with software applications.
  • Advanced DevOps Practices: Expanding my skills in CI/CD, Docker, Kubernetes, and cloud infrastructure, applicable to both AI projects and software development.

🎯 Areas of Interest

  • Cross-Platform Application Development in C#/.NET
  • MLOps & Workflow Automation
  • Computer Vision & AI for Software Applications
  • Data Science and Analytics
  • Agile Software Development Practices

🎮 Hobbies & Interests

  • Football ⚽ & Formula 1 🏎️: Big fan of football matches and Formula 1 races.
  • Chess ♟️: Enthusiastic chess player who enjoys the strategic challenges of the game.

📫 Let's Connect If you’re interested in collaborating, sharing ideas, or chatting about tech, feel free to connect with me on LinkedIn or drop me a message here!

🌐 Socials:

LinkedIn

💻 Tech Stack:

C# C++ HTML5 JavaScript LaTeX Python R YAML AWS Azure .Net Apache Spark FastAPI Flask Nodemon OpenCV Postgres Keras Matplotlib NumPy Pandas PyTorch scikit-learn TensorFlow GitHub GitLab CMake Jira Docker Kubernetes Postman

📊 GitHub Stats:



✍️ Random Dev Quote

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  1. VAE_vs_GAN VAE_vs_GAN Public

    Developed and experimented with linear, convolutional, and variational autoencoder (VAE) and GAN architectures for image generation, analyzing the performance in terms of reconstruction quality and…

    Jupyter Notebook

  2. Masterthesis Masterthesis Public

    Master thesis focuses on utilizing transfer learning techniques and object detection algorithms to analyze 3D LiDAR data, aiming to enhance the accuracy and efficiency of object recognition in auto…

    Jupyter Notebook 1

  3. Practical_Course_Overparametrized_Sigmoid_Autoencoder Practical_Course_Overparametrized_Sigmoid_Autoencoder Public

    Explored memory properties in neural networks using an overparameterized sigmoid autoencoder, including the role of attractor dynamics in encoding and retrieval processes.

    Jupyter Notebook

  4. 2D-Object-Detection 2D-Object-Detection Public

    This project demonstrates a simple web application using FastAPI for backend services and a basic HTML frontend. Users can upload images through the interface, which are then processed by the backe…

    Jupyter Notebook

  5. AI_Chatbot AI_Chatbot Public

    Python

  6. Weather-App Weather-App Public

    Weather App in C# and .NET 8: This project is a weather application built using C# and .NET 8, designed to provide real-time weather data. Future enhancements will include an AI component trained …

    C#