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rizwanahmed786508/README.md
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πŸŽ“ BS Software Engineering | CGPA 3.76/4.00 πŸ’Ό Machine Learning Intern @ National Grid Company Pakistan Limited πŸ“Š 5+ End-to-End Machine Learning Projects πŸš€ Machine Learning β€’ NLP β€’ Predictive Analytics β€’ Streamlit 🌍 Open to AI Research & ML Opportunities

🧠 About Me

I'm Rizwan Ahmed, a Software Engineering student at IBA Sukkur (CGPA 3.76/4.00), currently working as a Machine Learning Intern at National Grid Company Pakistan Limited (NGC).

I build production-oriented ML systems end-to-end β€” data collection, cleaning, exploratory analysis, feature engineering, model development, evaluation, and deployment. Each project in my portfolio ships as a working, deployed application rather than a static notebook.

My core interests are Machine Learning, Deep Learning, NLP, and MLOps, and I'm working toward a career as a Machine Learning Engineer alongside a longer-term interest in graduate-level AI research.



πŸŽ“ Education

πŸ›οΈ IBA Sukkur BS Software Engineering CGPA 3.76/4.00 Β |Β  Expected Graduation May 2027

Research Interests: Machine Learning Deep Learning NLP MLOps Explainable AI Predictive Analytics


πŸ’Ό Experience

Machine Learning Intern β€” National Grid Company Pakistan Limited (NGC) July 2026 – Present

β€’ Analyze operational datasets for predictive modeling

β€’ Develop Scikit-Learn models for real-world power sector use cases

β€’ Perform feature engineering and model evaluation

β€’ Present insights through technical reports and presentations

πŸš€ Featured Projects

πŸ“Š Employee Job Satisfaction Prediction

Problem: HR teams lack an early signal for declining employee satisfaction. Solution: Scikit-Learn classification model trained on workplace survey data to flag at-risk satisfaction levels.

Classification EDA Predictive Analytics Python Scikit-Learn Pandas Dataset: HR employee survey data Β |Β  Accuracy: 87.31%

Repo

πŸ’³ Credit Scoring System

Problem: Lenders need a fast, consistent way to assess borrower risk. Solution: Classification model trained on financial/credit history data, deployed as an interactive scoring app.

Classification Predictive Analytics Deployment Python Scikit-Learn NumPy Dataset: Financial/credit history records Β |Β  Accuracy: 83.12%

Repo Live Demo

πŸ—£οΈ Customer Review Analytics Dashboard

Problem: Manually reading customer reviews doesn't scale. Solution: NLP pipeline that extracts sentiment and key themes, surfaced through an interactive Streamlit dashboard.

NLP Dashboard Deployment Python Pandas Streamlit Dataset: Customer review text data Β |Β  Accuracy: 88.93%

Repo Live Demo

🩺 Diabetes Prediction System

Problem: Early risk detection can meaningfully change patient outcomes. Solution: Classification model on patient health metrics for early-detection screening, deployed as a live app.

Classification EDA Deployment Python Scikit-Learn Pandas Dataset: Pima Indians Diabetes dataset Β |Β  Accuracy: 75.95%

Repo Live Demo

🌐 MorpheLabs Landing Page

Problem: A brand needed a fast, modern web presence. Solution: Responsive landing page built with clean UI/UX principles, deployed on Vercel.

Frontend Deployment HTML CSS JavaScript

Repo Live Demo


πŸ› οΈ Tech Stack

Programming Languages

Python JavaScript HTML5 CSS3

Machine Learning

Scikit-Learn

Natural Language Processing

NLP

Data Analysis

Pandas NumPy

Deployment

Streamlit Vercel

Version Control

Git GitHub

Development Tools

VS Code Jupyter Google Colab


πŸ“ˆ GitHub Analytics

GitHub Streak

πŸ† Achievements

  • πŸ’Ό Machine Learning Intern @ National Grid Company Pakistan Limited
  • πŸ› οΈ Built 5+ end-to-end Machine Learning projects, each taken from raw data to deployed application
  • πŸš€ Deployed live ML applications on Streamlit and Vercel
  • πŸŽ–οΈ Introduction to Data Science β€” Cisco
  • πŸŽ–οΈ Intermediate Machine Learning β€” Kaggle
  • πŸŽ“ CGPA 3.76 / 4.00 in BS Software Engineering at IBA Sukkur

🎯 Current Focus

Machine Learning Engineering Β  AI Research Β  Natural Language Processing Β  Predictive Analytics Β  Open Source Contributions


🀝 Connect With Me

LinkedIn GitHub Kaggle Email


I build Machine Learning systems that turn data into reliable, real-world decisions. Open to Machine Learning internships, research collaborations, and engineering opportunities.

Always learning. Always building. Always improving.

Β© 2026 Rizwan Ahmed

Pinned Loading

  1. customer-review-analytics-dashboard customer-review-analytics-dashboard Public

    Designed and deployed an AI-powered sentiment analysis dashboard using Natural Language Processing and Machine Learning, enabling real-time review classification, model interpretability, and busine…

    Jupyter Notebook 1

  2. employee-job-satisfaction-prediction employee-job-satisfaction-prediction Public

    End-to-end Machine Learning project that predicts employee job satisfaction using Random Forest. Covers data cleaning, EDA, preprocessing, feature engineering, model evaluation, and visualization, …

    Jupyter Notebook 2