Ceyhun Kapucu

I have accumulated expertise in the following domains: • Python, SQL, NoSQL, Kafka, Redis, Nats.io, multi-threading/processing • Demand Forecasting & Time Series (Statistical and modern approaches) • Full Stack Machine Learning Apps • Feature Engineering • Recommendation Systems • Memory / User / Model-Based Collaborative Filtering • Automated Machine Learning • AI Agents / Workflow Automations • Production Level Data Science

I have been working as a software developer and as a lecturer in the Department of Informatics at a State University. Since 2013, I am working on Data Science and Machine Learning with Python. I have been using Python in many areas including Ph.D. and academic studies, and side projects (data scraping, ML model development, NLP, data science & analysis, automation, full-stack AI apps, and consulting). Also, I am lecturing IT lessons including Mobile and Full-Stack development, IoT & Cloud Computing.

For my Ph.D., I designed and developed a real-time photovoltaic fault diagnosis system based on the ensemble learning method. The system consists of the Python+Flask REST API backend running on the cloud and an embedded system-based IoT app/front-end including a sensor network. As a result of this study, three research articles were published. https://scholar.google.com/citations?user=ALOt5xIAAAAJ&hl=en

I developed a real-time web-based photovoltaic monitoring system in 2005 for my master's thesis. With the project, three PV systems in different locations were monitored and analyzed in real-time.