Sakinat-Folorunso/XAI-Tutorial

Interactive Explainable AI Notebooks for Data Science Africa 2025 # XAI Tutorials for Data Science Africa 2025 **Demystifying the Black Box: Hands-on Explainable AI for Health, Finance, and Agriculture** This repository contains a suite of interactive notebooks, slides, and supporting materials used in the XAI (Explainable AI) tutorial session facilitated by Dr. Sakinat Folorunso at Data Science Africa 2025. 👩🏾‍💻 **Facilitator**: **Dr. Sakinat Oluwabukonla Folorunso** Associate Professor of AI Systems and FAIR Data Science Artificial Intelligent Sytems Research Group Olabisi Onabanjo University, Ago-Iwoye, Ogun State, Nigeria Google Scholar | GitHub | Website | TRAIL 🔍 About Me: I am a researcher, educator, and AI community leader passionate about leveraging Artificial Intelligence, Machine Learning, and FAIR Data Science for health, culture, equity, and innovation in Africa. My work includes developing explainable AI systems for diagnostics, promoting AI literacy, and preserving indigenous knowledge using data science. # 🧠 Explainable AI (XAI) Tutorial with SHAP & LIME Welcome to the **XAI Tutorial Notebook** repository — a practical, hands-on guide for beginners and intermediate machine learning engineers to learn how to interpret model predictions using explainability techniques like **SHAP** and **LIME**. ## 🚀 About This Tutorial This tutorial introduces: - Feature-based explanation techniques for tabular classification tasks - Hands-on implementation of **SHAP (SHapley Additive exPlanations)** - Step-by-step demonstration of **LIME (Local Interpretable Model-agnostic Explanations)** - Visual comparison between SHAP and LIME on the same example - Real-world classification scenario (breast cancer diagnosis) 📘 The included notebook (`XAI_Tutorial_Notebook_1.ipynb`) walks through: - Dataset preprocessing - Training an ML model (XGBoost & RandomForest) - Applying SHAP & LIME explainers - Visualizing the output - Saving and comparing explanations ## 📈 Required Libraries To run this tutorial, install the following libr …