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christianchimezie/README.md

👋 Hi, I’m Christian Chimezie

💡 Data & AI Specialist | Open-Source Contributor | Educator & Mentor

I’m passionate about turning complex data and AI concepts into practical solutions that empower people and organizations to make better decisions. My journey spans data analysis, AI research, and process optimization, supported by an MSc in Artificial Intelligence and Data Science (Distinction).

🚀 What I’m Working On

  • Leading the development of PlotSense – an open-source Python package bringing explainable AI into data visualization.
  • Exploring innovative ways to make AI more transparent, accessible, and actionable for data professionals.
  • Creating resources and talks on AI in analytics, explainable AI, and the future of data-driven decision-making.

🤝 Community & Mentorship

  • Mentor at Generating Genius and GT Scholars, guiding the next generation of data and AI enthusiasts.
  • Advocate for open-source collaboration, with contributions to AI tools and educational projects.

🛠️ Tech I Work With

  • Languages & Tools: Python, SQL, Power BI
  • AI & Data: Machine Learning, Explainable AI, Data Visualization
  • Practices: PEP 8 compliance, CI/CD, Open-source development

🌍 Let’s Connect I’m always open to discussions on data, AI, and building meaningful open-source projects.


My mission: demystify AI, empower people with data, and build tools that make insights smarter.

Pinned Loading

  1. PlotSenseAI/PlotSense PlotSenseAI/PlotSense Public

    PlotSense is an AI-powered assistant that helps data professionals and analysts make smarter, faster, and more explainable data visualizations. Whether you're exploring a new dataset or building da…

    Python 355 159

  2. CREDIT-RISK-PREDICTION-THROUGH-ENSEMBLE-TECHNIQUES-AND-MODEL-AGNOSTIC-METHODS CREDIT-RISK-PREDICTION-THROUGH-ENSEMBLE-TECHNIQUES-AND-MODEL-AGNOSTIC-METHODS Public

    This study delves into artificial intelligence's (AI) transparency in credit risk prediction, explicitly focusing on four ensemble techniques and two model-agnostic methods.

    Jupyter Notebook