🐧 Predict penguin species using a machine learning app that analyzes physical traits and habitat for instant, insightful results.

Heart Disease prediction and Breast Cancer Detection

"oxayavongsa/projects" is a public GitHub repository serving as a diverse AI/ML Project Portfolio. Using Python coding and Juptyer notebook for multiple methodologies to model statistical algorithms.

This repository contains various Image Classification projects which have been built using TensorFlow.

An interactive ML web app predicting Titanic survival using features like age, sex, class, family size, and fare. Built with Python, scikit-learn, and Streamlit, it provides real-time predictions for educational and demo purposes.

An end-to-end machine learning project that predicts anxiety severity using classification models (Naive Bayes, Decision Tree, SVM, Logistic Regression, XGBoost), based on lifestyle, health, and behavioral features.

Comparing sampling techniques and classification algorithms to predict credit risk

Customer Churn Prediction Model & Data Pipeline

Air Quality Index (AQI) Prediction Using Random Forest Regressor(Sci-kit)

An experimental application for detection of plagiarism in source code using NLP techniques and Similarity Detection Algorithms

Trial activation analysis for a 30-day SaaS trial — behavioural event data, conversion driver analysis, dbt SQL models, and an interactive analytics dashboard. Built for the Splendor Analytics Data Analyst Challenge.

A website where users can find reviews about their favorite local coffee houses

☯︎ Simulate the winner of a hypothetical fight using machine learning

Open data analysis for the popular exam results by subject with Python, Pandas and MatPlotLib. Skews, biases, correlation and impact of the recent years on the state of the education system in Ukraine

A Data Science model that supports early-stage fraud flagging to reduce financial loses

Geospatial ML pipeline predicting river water quality across South Africa using satellite, climate, and terrain data. EY Open Science AI & Data Challenge 2026 — top 10%, R² = 0.44.

Developed deep learning neural network models using Python (tensorflow, scikit-learn) to predict whether non-profit organizations would be good candidates for donations

Using Python for Data Science

End-to-end churn prediction pipeline with SHAP explainability and a Streamlit web app. Built on the Telco Customer Churn dataset.

Project code for pedestrian detection using haar and hog cascade. Predicted via several machine learning methods.