Joshua Padron-Uy, Computer Science Department
Okanagan College, BC

Testing Data Pipeline Limits for Stock Market Forecasting with Machine Learning Integration

Time & Date: Wed. Apr. 23, 2025, 6:30 pm – 7:15 pm
Location: HS-301 and Zoom, Okanagan College, 1000 KLO Rd., Kelowna, BC, V1Y 4×8.
Registration: https://events.vtools.ieee.org/m/482426

Abstract:

This research aims to investigate the performance of a data pipeline system implemented using an extract, transform, load (ETL) tool under increased data volume. The system utilizes a data warehouse (DW) to support an XGBoost machine learning model for forecasting closing stock prices. The data source comes from the Financial Modelling Prep (FMP) API, which provides large amounts of real-time and historical data from the stock market.

Bio:

Joshua Padron-Uy is a fourth-year Computer Science student working on a research project in the COSC 448 Research Methodologies. He is an aspiring student seeking to work in the tech industry. He is eager to learn about various areas, including software engineering, DevOps, data science, and most recently, data engineering.

For further information, please get in touch with Youry Khmelevsky (email: Youry at IEEE.org) and subscribe to the news at okanagan@listserv.ieee.org
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