I’m Godfrey Purification, a full-stack developer who enjoys building reliable, scalable web applications end to end. I work across frontend and backend using React, Vue, Node.js/Express, and Python frameworks like Flask, Django, and FastAPI, and I also create REST APIs and GraphQL services. I’m especially interested in performance, security, and clean integration between the UI, services, and databases (Oracle and MongoDB).
Beyond coding, I bring strong automation and data/AI experience. I use tools like n8n to streamline workflows and integrate APIs, and I’ve worked with data science, machine learning, deep learning, and LLM integration. I also have leadership experience from serving as a Vice President, which strengthened my problem-solving, compliance mindset, and ability to drive outcomes—skills I apply directly to delivering software that meets real business needs.
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Handwritten Digit Recognition with Keras is a deep learning application that recognizes handwritten digits drawn on an interactive Tkinter canvas. Using the MNIST dataset, Keras, NumPy, and Pillow, the project trains a neural network to classify digits from 0–9. Custom preprocessing detects, crops, resizes, normalizes, and centers handwritten input before prediction. The application displays the predicted digit and confidence score, demonstrating the complete workflow from training to real-time AI prediction.
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