• 💼 LinkedIn:

I'm a Computer Science student at George Mason University and an AI Fellow at Break Through Tech in partnership. I’m passionate about applying Machine Learning to real-world problems, from sentiment analysis to image classification, with a strong foundation in Python, scikit-learn, and data-driven storytelling. I love exploring how data can tell stories and drive impactful decisions. My work spans from building classification models to preparing complex datasets for predictive modeling — always with an eye toward clarity, reproducibility, and practical application.

• 📧 Email: camilacs_6@hotmail.com
• 💼 LinkedIn

• What I Did: Partnered with Planned Parenthood Federation to analyze and augment chatbot data to improve sexual and reproductive health responses.
• Tools & Skills: Data analysis, binary classification, confusion matrix evaluation, model development, deployment considerations.
• Result: Delivered a predictive model capable of identifying chatbot cases needing improved responses.

• What I Did: Preprocesses Airbnb data, handles missing values, transforms categorical and numerical variables, and identifies relevant features for modeling.

• Tools & Skills: Python, Pandas, NumPy, data cleaning, feature engineering.

• Dataset Used: airbnbData_train.csv

• Skills: Data cleaning, feature engineering, Pandas, NumPy

• What I Did: Trained and evaluated classification models using Decision Trees and KNN, compared performance, and tuned hyperparameters for better accuracy.

• Tools & Skills: scikit-learn, hyperparameter tuning, model evaluation.

• Datasets Used: airbnbData_Prepared.csv, airbnb_readytoOHE.csv

• Skills: scikit-learn, hyperparameter tuning, model evaluation

• What I Did: Performed feature selection, evaluated the model with accuracy and confusion matrix, and discussed considerations for deployment in production.

• Tools & Skills: Feature selection (SelectKBest), evaluation metrics, deployment with pickle, precision-recall & ROC analysis.

• Dataset Used: airbnbData_train(2).csv

• Skills: Feature selection, evaluation metrics, deployment considerations

• What We Did: An AI-driven, PoseNet-powered interactive health education tool for kids, designed to make learning about wellness fun and engaging. Built as part of the H2AI Health Hackathon with AI, this project combines computer vision with educational content to encourage healthy habits in an interactive way.

• Skills: Pose estimation, AI-assisted interactivity, Node.js, Azure OpenAI, front-end integration.

A collection of projects covering the full Machine learning foundations, from data preprocessing to model deployment.

• Cloud deployment of ML models
• React + Django integration
• Advanced model tuning & feature engineering

• Machine Learning & Data Science
• Ethical AI & Algorithmic Fairness
• Database Design & Web Development
• Paddle boarding 🏄‍♀️
• Traveling & exploring new cultures ✈️
• Collecting pins from my trips 📍

I’m from Colombia 🇨🇴 and I love drinking hot chocolate with cheese!
It might sound unusual, but trust me — it’s delicious, especially with queso campesino or string cheese.