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.

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

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.

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

Customer Churn Prediction Model & Data Pipeline

Comparing sampling techniques and classification algorithms to predict credit risk

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

☯︎ Simulate the winner of a hypothetical fight using machine learning

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

Using Python for Data Science

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

Notes while learning to code in python

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

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

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

Prediction Car prices using a Linear Regression model

MediMind AI, Random Forest algoritması kullanarak semptom analizi yapan modern bir sağlık asistanıdır. React (Frontend) ve FastAPI (Backend) ile geliştirilmiştir. İnteraktif vücut haritası, karanlık mod desteği ve PDF raporlama özellikleri sunar. Tamamen Türkçe ve kullanıcı dostudur.