Machine Learning

Projects were done under the mentorship of Dr. Christopher Monterola and Dr. Erika Legara.

In this course, students are introduced to the world of machine learning and predictive analytics. This is a hands-on and an application-heavy module, where they look at real-world data and cases in different fields. Students acquire the basic machine learning skills including hyper tuning of parameters and model evaluation. In addition, they are familiarized with the best practices in predictive analytics including how to properly evaluate models. The most important aim of this course is for students to have a clear framework on how to build mental models using machine learning.

Bantay Balita: Using Machine Learning to Wipe Out Misinformation

Bantay Balita aims to be a demonstration in using machine learning as an impartial and data-driven tool to classify and understand misinformation. We cannot simply tag from the source because in today

J. Allon-Pineda, H. Bayaborda, H. Buitre, J. Gonzales, M. Pingol, C. Soriano

Community Pan-Tweet: A Data Science Exploration of the Virality of the Community Pantry Phenomenon on Twitter

Social media, such as Twitter, seemed to have played a key role in communicating the importance and need for community pantries, between the time that Ms. Non set up the Maginhawa Community Pantry on

R. Chan, R. Dela Cruz, P. Donato, P. Guevara, S. Mendoza, F. Rara, A. Santiago

Deal or No Deal: Valuing businesses through Machine Learning

The practice of valuation is integral in business. Some selected applications include buying and selling startups for entrepreneurs and companies, raising capital for business owners, and assessing th

W. Diamada, K. Inocencio, D. Nuesca, K. Reyes, J. Tan, M. Verdeprado

How Much Does the Sexiest Job Pay? A prediction of the Stackoverflow data scientists’ salary

Data Science created a huge buzz as it combines multiple fields like statistics and artificial intelligence to enable a new age of learning and innovation, dubbing it as the sexiest job of the 21st ce

M. Acot, J. Gacal, Z. Ginez, M. Hao, M. Mapa, J. Las

Where Is the Love? Identifying Hate Speech in Philippine Election-Related Tweets

Increased usage of social media, particularly during election seasons, has intensified political division and hate speech. In line with this, a study was conducted to build a model that would automati

M. K. A. Baluyut, M. dela Resma, A. R. Fernando, N. Lapid, S. R. Sy, A. Timajo

Anong Say ng Presidente Mo? Finding Patterns in the Presidentiables’ Tweets

As campaigns ramped up for the Philippine presidential election on May 9, 2022, the voting public was eager to learn more about the candidates’ platforms and political positions. Social media can be

G. Cadena, A. Changcoco, P. La Rosa, M. Paderes, G. Piquero, B. Ruiz

Prevention is Better than Cure: Predicting Illegal Drug Vulnerability among Filipino Youth

Illegal drugs are one of the most important issues in the Philippines and has destroyed the lives of innocent people because of the effects of drug abuse such as child abuse, domestic violence and cri

J. Buño, A. de Guzman, R.F. Rivera

Beating the Philippine Stock Market: A Machine Learning Approach to Portfolio Management

The stock market is one of the ways a person can earn passive income, and there have been many attempts to look for the holy grail, the trading strategy that can consistently yield profits for the inv

P.E. Ang, C. Antioquia, A.N. Carpio, J. Dolorso, C.R. Patalud

Day-ahead Power Demand Forecasting of Luzon Power Grid using Gradient Boosting Regression Trees

Reliable forecasting of electricity demand is key to ensuring sustainable supply-demand systems in the energy sector. Various approaches to improve reliability of forecasts range from the classical ti

M. Dorosan, J.A. Edeza, J. Gonzales, C. Licong, J. Manansala, R. Marquez

PUTTING THE AI IN TRAIN: Predicting Passenger Volume of MRT-3 Using its Surrounding Amenities

Mass urban transit has been considered a sustainable and efficient transport solution to developing megacities like Metro Manila, which are experiencing challenges due to rapid motorization, chronic t