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TheMuhammadAsad/README.md

Hi, I'm Muhammad Asad

Energy Data Analyst, Data Scientist and Web Developer.

I build statistically rigorous analysis, production-shaped ML pipelines, and full-stack data products, with a research background spanning peer-reviewed publications and international conference presentations. I also design and ship client websites as a freelance web developer.

themuhammadasad.github.io → is my full portfolio: 13+ data/ML projects, 7+ websites, experience, publications, and certifications.


Featured projects

Project What it does
Energy Intelligence Platform Full-stack app over 25 years of European electricity-mix data, built with FastAPI + PostgreSQL, Next.js/TypeScript, Docker Compose, and CI
Credit Card Fraud Detection Real transaction data under 0.17% class imbalance; cost-based threshold optimizer, live Streamlit dashboard
A/B Testing: Mobile Game Retention SRM check, two-proportion z-tests cross-validated against bootstrap resampling, a peeking-problem simulation
Image Classification: CNN vs. Transfer Learning CNN from scratch vs. MobileNetV2, augmentation ablation, Grad-CAM analysis
Oil Production Decline Curve Analysis Classical petroleum-engineering Arps decline models on 60 years of real production data

Skills

Data & Visualization Python (pandas, NumPy, scikit-learn) · R · SQL · Power BI · Streamlit · Plotly · Tableau ML & Statistics XGBoost · TensorFlow/Keras · SHAP · hypothesis testing · predictive modelling Web Development React · Next.js · TypeScript · FastAPI Tools & Platforms Docker · Kubernetes · PostgreSQL · Git

Get in touch

Portfolio LinkedIn Email Google Scholar

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  1. energy-intelligence-platform energy-intelligence-platform Public

    Full-stack energy data platform: FastAPI + PostgreSQL + Next.js/TypeScript, trend forecasting, Docker Compose, GitHub Actions CI

    TypeScript

  2. customer-churn-prediction customer-churn-prediction Public

    ML churn prediction with model comparison, SHAP interpretation, and cost-based retention campaign economics

    Jupyter Notebook

  3. energy-demand-forecasting-deep-learning energy-demand-forecasting-deep-learning Public

    60-min-ahead energy demand forecasting: naive baseline vs regularized XGBoost vs LSTM, with a documented overfitting diagnosis and fix

    Jupyter Notebook

  4. energy-transition-dashboard energy-transition-dashboard Public

    Interactive Streamlit + Plotly dashboard over 24 years of European electricity-mix data

    Python

  5. europe-energy-transition-analysis europe-energy-transition-analysis Public

    Python/pandas analysis of Europe's electricity decarbonization, 2000-2024: EDA, hypothesis testing, and trend projection on OWID data

    Jupyter Notebook

  6. oil-production-decline-analysis oil-production-decline-analysis Public

    Petroleum engineering decline curve analysis (Arps models) applied to 60 years of country-level oil production data

    Jupyter Notebook