Aspiring Data Scientist/ML Engineer

Education

Research Assistant @ University of Santo Tomas (April 2024 - Present)

Trained a multiclass Support Vector Machine Model on data gathered from the iSULAT Pen to detect and classify alphanumeric characters during handwriting using Python.
Trained a YOLO Model on ultrasound images and developed a software application to deploy the machine learning model for local hospital use via Python.

📚 What Makes a Good Book?
- This project builds a binary classification model to determine whether a book is “Popular” or “Unpopular” based on price, review helpfulness, authors, and categories.
📊 Predictive Modeling for Agriculture
- This project analyzes soil nutrients (Nitrogen, Phosphorus, Potassium) and pH levels to predict the best crop type using Logistic Regression. I used hyperparameter tuning (GridSearchCV) to improve model accuracy by optimizing regularization and solver selection.
🤖 Facial Recognition with Supervised Learning
- This project leverages machine learning to enhance the security of influential figures by distinguishing Arnold Schwarzenegger from others. The goal is to build multiple classification models and determine the best-performing one based on cross-validation scores.
🏠 Data Driven Product Management: Conducting a Market Analysis
- This project aims to predict daily power consumption in a given area using machine learning models. The dataset contains features such as date, year, semester, day of the week, week in the year, day in the year, and month. Two machine learning models, Random Forest Regressor and XGBoost Regressor, are trained to make accurate predictions of power consumption.