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AliSajid55/README.md

Hi there, I'm Ali Sajid 👋

AI Engineer | Deep Learning | Computer Vision | GEN AI

I'm an AI Engineer with a strong focus on Deep Learning, Computer Vision, NLP, GEN AI and Explainable AI (XAI),
currently pursuing a Master’s in Artificial Intelligence. I work at the intersection of research and production,
building intelligent systems that are both interpretable and scalable.

Strong foundation in programming, algorithms, and data structures, with hands-on experience in machine learning, deep learning, and transformer-based models using Python and PyTorch. Familiar with building AI solutions from research prototypes to deployable systems, with exposure to FastAPI-based model serving, MLOps pipelines, and cloud infrastructure like AWS. Experienced in computer vision, NLP, and data-driven modeling, and eager to grow in a production-oriented AI engineering role focused on scalable and reliable systems.

📍 Islamabad, Pakistan | 🌍 Open to Remote, On-Site & Global Opportunities

🌐 Connect With Me:

LinkedIn GitHub Email

💻 Tech Stack:

Python Flutter Dart

FastAPI Flask PyTorch TensorFlow OpenCV Pandas NumPy MongoDB

Tailwind CSS React React Native JavaScript

AWS Google Cloud Redis

Docker Git GitHub Actions

“ Impossible is a word to be found only in the dictionary of fools.” — Napoleon Bonaparte

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  1. faithful-counterfactual-explanation-ViT faithful-counterfactual-explanation-ViT Public

    Explainable Artificial Intelligence (XAI) focuses on making deep learning models transparent and trustworthy by explaining their decisions. FCET investigates attention heads-level counterfactual ex…

    Jupyter Notebook

  2. SAM-BrainTumor-Segmentation SAM-BrainTumor-Segmentation Public

    Segment Anything Model implementation and dashboard for brain tumor segmentation using medical images.

    Jupyter Notebook

  3. flutter-the-learner flutter-the-learner Public

    A beautifully designed cross-platform educational app built using Flutter, offering interactive content, multi-language support, and seamless learning experience across Android, iOS, Web, and Desktop.

    Dart

  4. student-performance-analysis-1st-work- student-performance-analysis-1st-work- Public

    EDA + ML classification with four models (SVM, Decision Tree, KNN and Random Forest) on student exam performance dataset

    Jupyter Notebook

  5. IMDB-Movie-Review-Sentiment-Analysis IMDB-Movie-Review-Sentiment-Analysis Public

    This project performs sentiment analysis on movie reviews from the IMDB dataset using NLP techniques and machine learning models such as Logistic Regression, Naive Bayes, and Random Forest.

    Jupyter Notebook

  6. Final_Task_PAI Final_Task_PAI Public

    This is the final evaluation assignment of subject: Programming for Ai

    Jupyter Notebook