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Hi there 👋

My name is Ali Habibullah, and welcome to my GitHub profile!

I'm a passionate Software Developer 🧑‍💻 with an interest in machine learning 🤖, currently diving deep into innovative solutions in both fields. I'm currently living the developer life at Lyrae Digital, and I've also spread some knowledge as a Teaching Assistant at KAUST. 🎓 I graduated with a Bachelor's Degree in Computer Science from King Abdulaziz University, flaunting a GPA of 4.98/5. 🏆

Here's a sneak peek of the technologies I often use:

  • Programming Languages: Python, C#, Java, PHP 🚀
  • Frameworks: Django, Laravel 🌐
  • Cloud Technologies: Azure, Kubernetes ☁️
  • Machine Learning: Keras, TensorFlow, PyTorch, Pandas 🧠

Feel free to reach me on LinkedIn 😄. Let's connect, collaborate, and create something awesome together!

Ali Habibullah's Projects

badapple icon badapple

Image to text for the popular Bad Apple meme lol.

en-ar-translator icon en-ar-translator

EN-AR Translator built using a transformer model, and published using Django

nlp-project-sentiment icon nlp-project-sentiment

This application performs sentiment analysis using a Deep CNN model built with TensorFlow. It provides a GUI where users can enter text and see whether the sentiment is positive or negative.

opengl_game icon opengl_game

Astro man, a game build on Java OpenGL, not optimized, but it works!

review-it icon review-it

"Review IT" is an entertainment review platform offering insights on movies, games, TV shows, and anime, with various features like trailers, user feedback, and user reviews, built using Laravel for the backend and Bootstrap & Tailwind CSS for the frontend.

royal-defenders icon royal-defenders

Royal Defenders is a strategic Tower Defense Game developed in Unity, where players protect a kingdom using various towers, enriched by three distinct pathfinding algorithms: Breadth First Search, Uniform Cost Search, and A* Search.

youtubeplaylistdownload icon youtubeplaylistdownload

This Python script allows you to download entire playlists from YouTube either as video files or as audio files. It utilizes multiprocessing to speed up the download process by downloading multiple files in parallel.

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