Bernard Relucio
Statistics. Data Science. Problem Solving.
About
Hello! I'm Bernard, a budding data scientist who is passionate about finding data-driven solutions to problems. I was trained under the data science bootcamp of Eskwelabs where I was equipped with practical knowledge on programming and various modeling techniques, from classification models and recommender engines to natural language processing algorithms. I am also formally trained in statistics, inculcating me with data knowledge foundations on the theoretical level.Outside data, I am a passionate leader, a writer, and music enthusiast. Don't ask me to sing, though — you most definitely will regret it!
Data Science Projects
From being a fellow in the data science bootcamp of Eskwelabs, an online data upskilling school, I currently have 5 data science projects under my belt. Explore them below! (Disclaimer: the data used for the projects were utilized for educational purposes only.)
1) Give Credit Where Credit Is Due: Raising Business Value Through Clustering
This project utilized k-means clustering in order to categorize customers based on credit card transaction behaviors in order to get a better view on how to improve business revenues. Click this photo above to see the full report.
2) Let It Flow (Wisely): A Research Study on Philippine Household Cashflow Management in 2021
This study employs classification modelling in order to categorize a household as a positive or negative cashflow household. In the process, the primary features contributing to this distinction are also determined. Click the photo above to see the full report.
3) SB19: Brining Pinoy Pop to the World
In this music streaming analytics project, time series analysis and recommendation engine modelling were utilized to analyze the current standing of SB19, a Filipino boy band, in terms of their music streaming performance, laying the foundations for possible strategies to encourage more listeners to support the band. Click the photo above to see the full report.
4) TeenTalks: Unmasking Depression in Textual Expression
For this project, natural language processing algorithms were used to analyze the social media posts of people ultimately identifying the main stressors of high school students and creating a tool that determines potential depressive tendencies of high school students through textual context. Click the photo above to see the full report.
5) Watts Up, 'Pinas?: Illuminating Insights in the Electricity Spot Market with K-Means Clustering and Time Series Analysis
In this capstone project, classification modelling and time series forecasting were used to analyze the bidding trends of different power plants in the Philippines, identifying the nature of different energy technologies which will be useful for policy-making in order to forward the net-zero carbon agenda all while maintaining and even decreasing the electricity cost being paid by Filipinos. Click the photo above to see the full report.
Get in touch
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