sci-kit-learn

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.

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.

CodeLab: SUT Machine Learning Community

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.

Comparing sampling techniques and classification algorithms to predict credit risk

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

Customer Churn Prediction Model & Data Pipeline

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

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.

AI-powered revenue recovery system that combines recoverability prediction, economic optimization, deterministic guardrails, and bounded workflows for failed and at-risk payments.

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

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

🏏 IPL Roster Optimizer - It Is A full-stack AI-powered web application that helps IPL teams optimize their player rosters, identify undervalued talent, and make data-driven decisions about trades and contracts with help Machine Learning & Predictive Models.

Using Python for Data Science

ML analysis of 284K+ transactions - 94% fraud recall using SMOTE and logistic regression

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.

A machine learning project that analyzes feature influence using Explainable AI techniques such as SHAP and LIME to improve model interpretability and transparency.

Uses unsupervised learning to cluster remote workspaces based on ambient noise and environmental factors for enhanced focus.

The first step if you're new to machine learning.