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  • Student / Aspiring AI Engineer
  • Karachi, Pakistan

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AyaanHussain1/README.md

Hi, I'm Syed Ayaan Hussain 👋

AI/ML Engineer in the making — I build things that ship, not just notebooks that run.

Typing SVG

🧭 About Me

  • 🎓 BSCS student at Iqra University, Karachi — building toward a career in AI/ML engineering
  • 🛠️ Currently interning at Ezitech Software, building the backend for an AI-powered recruitment & talent discovery platform (resume parsing, portfolio scoring, job matching, ATS reporting)
  • 🧠 I build full-stack RAG systems — most recently CodeSage, a multi-surface (web + Chrome extension + Electron desktop) tool for querying YouTube transcripts and local codebases
  • 📊 6+ deployed ML projects spanning classification, regression, and NLP — each with real, reported accuracy metrics (not cherry-picked)
  • 🏆 Competed in SkillVerse 2026 AI Rapid Forge and completed data science assessments with Zidio Development
  • 🌱 Currently deepening my knowledge of LangChain internals, Docker, and production ML deployment
  • ⚡ Fun fact: I train calisthenics (handstand progression) with the same iterative, track-what-works mindset I bring to debugging models

🚀 Featured Projects

🧩 CodeSage Full-stack RAG system for querying YouTube transcripts & local codebases. Three client surfaces: Chrome extension (Manifest V3), Electron desktop app, and web app. LangChain FAISS FastAPI OpenAI Embeddings Deployed: Railway (backend) + Vercel (frontend)

🎯 AI Talent Discovery Platform (Ezitech) Backend for an AI recruitment platform: GitHub data extraction, resume parsing (pdfplumber + GPT-4o-mini), portfolio scoring, and skill-overlap job matching. FastAPI Instructor Pydantic Streamlit

🩺 ASD Prediction Autism spectrum disorder screening classifier. XGBoost — 93% accuracy

💳 Credit Card Fraud Detection Imbalanced-classification fraud detection pipeline. Scikit-learn — 93% accuracy

📩 SMS Spam Classifier NLP text classification with NLTK preprocessing. Naive Bayes NLTK — 96.8% accuracy

🚗 Car Price Predictor Regression model deployed with an interactive UI. Scikit-learn Streamlit — R² ≈ 0.74

📁 15+ additional ML projects on my GitHub — each with a standalone .py implementation, documented README, and reported metrics (no notebook-only repos).

🛠️ Tech Stack

Languages & Core Python SQL

ML / Data Science NumPy Pandas Scikit-learn TensorFlow XGBoost

AI / LLM Engineering LangChain OpenAI FAISS

Backend & Deployment FastAPI Streamlit Railway Vercel Docker

Tools Git VS Code

📊 GitHub Stats

📈 What I'm Focused On Right Now

  • Deepening production-grade RAG architecture (retrieval quality, chunking strategy, evaluation)
  • Learning Docker for reproducible ML deployment
  • Shipping a personal portfolio site with live project demos and an inline resume viewer
  • Applying for AI/ML internship and junior engineering roles — open to opportunities

Every repo here has a working .py entry point, a real README, and a metric I can defend in an interview.

Popular repositories Loading

  1. CodeSage_Agent CodeSage_Agent Public

    AI agent that answers questions about YouTube tutorials and your own codebase — available as a Chrome extension, desktop app, and web app.

    JavaScript 1

  2. Rag-Agent Rag-Agent Public

    LearnShift AI turns static Java OOP content into a personalized AI tutoring experience that supports both learners and educators.

    Python

  3. Autism-Prediction Autism-Prediction Public

    ML web app predicting Autism Spectrum Disorder traits from AQ-10 screening responses. Built with XGBoost (93% accuracy), Streamlit, and scikit-learn. Supports single and batch predictions.

    Jupyter Notebook

  4. Credit-Card-Fraud-System Credit-Card-Fraud-System Public

    ML web app detecting fraudulent credit card transactions using Logistic Regression (93% accuracy) on a highly imbalanced real-world dataset. Built with scikit-learn and Streamlit, using undersampli…

    Python

  5. Book-Recommendation-System Book-Recommendation-System Public

    Book recommendation web app using item-based collaborative filtering (K-Nearest Neighbors, cosine similarity) on 1.1M+ user ratings. Built with scikit-learn and Streamlit.

    Python

  6. Car-Price-Predictor Car-Price-Predictor Public

    Car price prediction web app using Linear Regression (0.74 CV R²), selected via fair cross-validation over Random Forest and Gradient Boosting. Built with scikit-learn and Flask, with dynamic compa…

    Jupyter Notebook