A Data Scientist and Machine Learning Engineer developing intelligent systems powered by data.
Hi, I'm Clinton Beyene, a data scientist with a background in Python programming. I enjoy figuring out how things work—whether it’s good coding practices, engineering techniques, or machine learning methods. My work mainly involves building machine learning applications, analyzing data, and creating visualizations to uncover insights. I’m a firm believer in open-source collaboration, as I see shared solutions as a way to drive innovation within the community. Python is my go-to tool for daily work, helping me develop efficient and scalable solutions. Beyond data science, I’m deeply interested in endurance sports and healthy living. You can find my work on my website, including GitHub code, professional reports, and interactive visualizations. Thanks for visiting—I hope you find something inspiring!Clinton BeyeneA lightweight machine learning pipeline designed for CubeSat image classification, optimizing data transmission efficiency in space. This project integrates preprocessing, model training, pruning, quantization, and evaluation to enable real-time decision-making onboard resource-constrained satellites. Inspired by the VERTECS mission, it ensures high accuracy while minimizing computational costs.
A machine learning model developed to predict credit risk and assign credit scores, supporting data-driven lending decisions for Bati Bank's Buy-Now-Pay-Later (BNPL) service in collaboration with an eCommerce platform.
This project leverages machine learning to detect fraudulent transactions in e-commerce and banking, aiding in proactive security and risk management. The goal is to provide a robust fraud detection pipeline with explainability, deployment, and dashboard visualization for actionable insights.
A comprehensive data warehouse solution for Ethiopian medical business data scraped from Telegram channels, including data scraping, object detection with YOLO, and ETL/ELT processes.
Building interactive quiz application built with ipywidgets, powered by Google's Gemini AI model to enhance learning. It helps users self-assess their knowledge of Data Science and Gen AI.
Machine Learning is a subset of artificial intelligence techniques where computer models use data to learn and make decisions rather than following explicit programming logic. In machine learning, algorithms are trained on data to produce models that can be applied to new data. Think of these algori