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MuhammadAliEjaz1 (Muhammad Ali Ejaz) · GitHub

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MuhammadAliEjaz1/README.md

Hi, I'm Muhammad Ali Ejaz 👋

ML/AI Engineer | Data Science | Building Production-Grade AI for Real-World Problems

Final-year BS Data Science student at The Islamia University of Bahawalpur, building end-to-end AI systems — from model to deployment — with a focus on real impact in agriculture, public health, and disaster resilience across Pakistan.

🚀 Featured Projects

🌾 CropGuard AI Live crop disease detection platform for Pakistani smallholder farmers.

  • 6 deep learning models (EfficientNetB0), 94.3% avg. accuracy across 51 diseases, 6 crops
  • Trained on 45,000+ real field images — rejected lab-condition datasets for real Pakistani field conditions
  • Bilingual Urdu/English AI advisory via Gemini 2.5 Flash
  • Stack: TensorFlow, FastAPI, React, Docker, Hugging Face Spaces

🌊 Flood Risk Prediction Geospatial ML pipeline predicting flood risk across Punjab & KPK, Pakistan.

  • Satellite + weather data (Sentinel-2, SRTM DEM, CHIRPS rainfall) via Google Earth Engine
  • XGBoost classifier — F1 0.52, ROC-AUC 0.912, validated against real 2022 flood extent data
  • Interactive dual risk-map (predicted vs. actual) + 4-tab Streamlit app
  • Stack: XGBoost, GeoPandas, Google Earth Engine, Streamlit, Folium

🌽 Mandi Price Forecasting 7-day-ahead wholesale crop price forecasting for Punjab, Pakistan.

  • Playwright-scraped real government market data
  • LightGBM benchmarked against a naive baseline
  • Live Streamlit demo
  • Stack: LightGBM, Playwright, Streamlit

🚗 Used Car Price Predictor Fair-price predictor trained on real scraped Pakistani market data.

  • Scraped ~3,900 live PakWheels listings; engineered Pakistan-specific features (import/assembly status, registration province)
  • Tuned XGBoost — 9.9% MAPE, with honest per-segment error analysis
  • Stack: Scikit-learn, XGBoost, BeautifulSoup, Streamlit

❤️ Heart Disease Prediction Heart disease risk classifier with a full model comparison.

  • 5-model comparison; tuned Random Forest — 0.96 AUC
  • Streamlit demo app
  • Stack: Scikit-learn, Random Forest, Streamlit

🤖 CortexIQ AI-powered data analytics platform.

  • Upload a dataset, chat in plain English, get auto-generated Python analysis
  • Automated ML model comparison + branded PDF reports
  • Stack: FastAPI, Next.js, Groq, Scikit-learn, XGBoost

⛵ Yacht Hydrodynamics — Resistance Prediction
Residuary resistance prediction on the UCI Yacht Hydrodynamics dataset — 7-model comparison, physics-informed feature engineering, and an honest write-up of where hyperparameter tuning did (and didn't) help.
Stack: XGBoost, Optuna, SHAP

🛠️ Skills

Languages:

ML / Deep Learning:

Data & Analytics:

AI Engineering:

Tools & Deployment:

🏆 Achievements

  • 🎖️ 98.1 percentile — National Skill Competency Test (NSCT), conducted by HEC Pakistan in collaboration with MoITT, PSEB & P@SHA — 33,000+ candidates nationwide

Pinned Loading

  1. cropguard-ai cropguard-ai Public

    AI-powered crop disease detection platform for Pakistani farmers — 94.3% accuracy across 51 disease classes

    JavaScript 1

  2. cortexiq cortexiq Public

    AI-powered data analytics platform — upload a dataset, chat in plain English, and get auto-generated Python analysis, ML model comparisons, and branded PDF reports. FastAPI + Next.js + Groq.

    Python 1

  3. rxguard rxguard Public

    A safety-first RAG assistant for Pakistani medicine info — combines DRAP drug registration data with openFDA clinical data, with a hard architectural safety gate that blocks personalized medical ad…

    Python 1

  4. yacht-hydrodynamics-prediction yacht-hydrodynamics-prediction Public

    Residuary resistance prediction on UCI Yacht Hydrodynamics dataset — physics-informed feature engineering, 7-model comparison, and an honest finding that Optuna tuning doesn't beat the default Grad…

    HTML 2

  5. flood-risk-prediction flood-risk-prediction Public

    Geospatial ML system predicting flood risk in Punjab & KPK, Pakistan, using satellite imagery, elevation, and rainfall data — validated against the 2022 floods. XGBoost model (F1 0.52, ROC-AUC 0.91…

    HTML 1

  6. heart-disease-prediction heart-disease-prediction Public

    Heart disease risk classifier — 5-model comparison, tuned Random Forest (0.96 AUC), Streamlit demo app.

    HTML 2

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