Claire Mendoza

hi, i'm claire.

I build intelligent solutions with data.

A final-year Computer Science student specializing in AI, passionate about the entire data lifecycle—from engineering and modeling to creating actionable insights.

Say Hello!

/ about me

Claire Antonette Mendoza

Claire Antonette Mendoza

Makati City, Metro Manila

I'm a final-year student pursuing a Bachelor of Science in Computer Science, Specializing in A.I. at Mapúa University. My academic journey has been focused on bridging the gap between theory and practice by building complete, functional data solutions from the ground up.

I thrive on the entire data lifecycle: from acquiring and cleaning messy, real-world data to building predictive models and creating beautiful, insightful visualizations. My projects reflect this passion, showcasing my ability to not only analyze data but to build the very systems that generate it.

Technologies I've been working with:

Data Science & ML
Pandas Scikit-learn NumPy Matplotlib Seaborn XGBoost Hugging Face
Databases & BI
PostgreSQL SQL Power BI ETL
Web Development
JavaScript HTML & CSS Node.js Streamlit

/ projects

Salon Analytics Platform

An end-to-end system with a Node.js backend and Power BI dashboard. Includes an ML model to predict client no-shows with 89% accuracy.

Full-Stack•Machine Learning•Power BI

Kaggle: House Price Prediction

Advanced regression on a complex dataset. Performed deep feature engineering and trained an XGBoost model with a top RMSE of ~0.12.

XGBoost•Feature Engineering•Streamlit

Infectious Disease Analysis

Scraped a unique dataset using BeautifulSoup and built a classification model to predict diseases from symptoms with 96.5% accuracy.

Web Scraping•Classification•Power BI

Emotion Detection

A data science project using supervised machine learning to detect emotions from text data and a Kaggle dataset using Image Preprocessing, built with Python and the Kaggle API.

NLP•Supervised Learning•Kaggle API

Ghibli Website Refinement

A refined, personal take on Studio Ghibli's website—built with HTML, CSS, and JavaScript. Fully responsive and inspired by the studio's timeless aesthetic.

Frontend Dev•HTML/CSS•JavaScript

NLP Sentiment Analysis

A project using a pre-trained DistilBERT model and the Hugging Face library to perform sentiment analysis on the IMDB movie review dataset, achieving 88.1% accuracy.

NLP•Hugging Face•Deep Learning