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lesley-2198/README.md
Typing SVG

Hey, I'm Lesley Ngcobo

🧠 Data Scientist • 🤖 Full-Stack Web Developer • 📊 Insight Architect
Transforming complex data into actionable intelligence

Snake eating my contributions

🚀 About Me

Coding GIF

🎓 Academic Foundation: Information Technology @ Nelson Mandela University
🔬 Core Expertise: Machine Learning, Statistical Analysis & Data Storytelling
💡 Philosophy: "The best models aren't just accurate - they're understood"
🎯 Mission: Building interpretable AI systems that drive real business value
🌟 Passion: Turning complex datasets into compelling insights and actionable solutions

🔗 Portfolio: lesleyngcobo.netlify.app - Explore my complete project showcase

💼 Featured Projects

🎯 DataQuest Recommender 🛡️ Fraud Detection System 🏥 Madiba HealthConnect 📊 Portfolio Website
Hybrid ML Recommender Advanced Fraud Detection Healthcare Management Platform Client Portfolio Site
Collaborative filtering + content-based algorithms for personalized recommendations Imbalanced classification with ensemble learning and real-time monitoring Full-stack digital health app for patient records, appointments, and clinician workflows Modern responsive design with SEO optimization
R recommenderlab Machine Learning R Power BI XGBoost SMOTE ASP.NET Core 8 Angular Node.js HTML5 CSS3 JavaScript
View Project → View Project → View Project → • Live Demo → View Live →

🔑 Project Impact Highlights

  • DataQuest Recommender:
    🏆 Item-Based Collaborative Filtering (IBCF) outperformed all models with 22× higher precision and 15× higher recall than UBCF.
    🌍 Final deployed Full Hybrid balanced accuracy with contextual signals (region + season) for real-world adaptability.

  • Fraud Detection System:
    ⚡ XGBoost achieved 79% recall and 94% precision, minimizing false alarms while catching most fraud cases.
    📈 Improved recall by ~17% compared to baseline logistic regression, making fraud detection both accurate and practical.

🛠️ Technical Arsenal

🐍 Core Data Science Stack


R & RStudio
Python
Tidyverse
ggplot2
recommenderlab

📊 Data & Analytics Platforms


Power BI
Excel
MySQL
SQL Server
SSMS

🌐 Development & Design


Angular
HTML5
CSS3
JavaScript
ASP.NET

🎯 Current Focus Areas

graph TD
    A[🧠 Machine Learning Mastery] --> B[🔍 Hybrid Recommender Systems]
    A --> C[🛡️ Fraud Detection Models]
    A --> D[📊 Ensemble Methods]
    
    B --> E[Collaborative Filtering]
    B --> F[Content-Based Systems]
    
    C --> G[Imbalanced Classification]
    C --> H[Real-time Monitoring]
    
    D --> I[Random Forests]
    D --> J[XGBoost Optimization]
    
    style A fill:#64ffda,stroke:#0f0f23,color:#0f0f23
    style B fill:#4ecdc4,stroke:#0f0f23,color:#0f0f23
    style C fill:#ff6b6b,stroke:#0f0f23,color:#0f0f23
    style D fill:#ffd93d,stroke:#0f0f23,color:#0f0f23
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Contribution Graph

💡 "The best models aren't just accurate - they're understood."

🚀 Ready to collaborate? Let's turn insights into action with data-driven intelligence!
📬 Get in touch: Portfolio • Email • LinkedIn

Profile Views GitHub Followers

⚡ Made with ❤️ and lots of ☕ by Lesley Ngcobo
Last updated: August 2025 • Data Scientist & ML Specialist

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  1. CreditCardFraudDetection CreditCardFraudDetection Public

    An end-to-end machine learning project that identifies fraudulent credit card transactions using imbalanced classification techniques in R. The project applies logistic regression and ensemble mode…

    R 2

  2. DataquestRcSys2025 DataquestRcSys2025 Public

    A recommender system that predicts which products each user will like or engage with to personalize recommendations which will in turn increase user satisfaction, engagement, and, ultimately, reven…

    R 1

  3. PropertyQuest PropertyQuest Public

    A website where users can rent, buy or sell their property

    TypeScript 1

  4. Madiba-HealthConnect Madiba-HealthConnect Public

    A tele-consultation healthcare platform designed to bridge the gap between patients and healthcare providers. It uses a triage system to assess patient needs, enabling faster, more efficient access…

    HTML 1