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.

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

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

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

Comparing sampling techniques and classification algorithms to predict credit risk

Using Python for Data Science

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

Used Python (scikit-learn) to develop supervised machine learning models to predict credit risk

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

This is a Python Simple Linear Regression project that takes in an excel spreadsheet with 2 continuous variables, one independent and the other dependent, and it'll split the data into training and test data on 80/20 ratio. We use the training data to create a model then we use the test data to calculate the Mean Square Error of the model.

This predicts that will a previous donor donate blood in a given month or not

Exploratory-Data-analysis-heart-failures-obesity-levels-car-sales-online-education-adaptibilty|| Jupyter|| pythons||Numpy|| Pandas

Machine Learning model that predicts the risk of early readmission to the hospital for diabetic patients (within 30 days).

In-class work from Data Science 101 at Pomona College

classifical between Brahms, Beethoven, Bach , and Schubert MIDI Audio Files

Used Python and unsupervised machine learning to create a report of cryptocurrencies being traded and classify them using unsupervised machine learning

Prediction Car prices using a Linear Regression model

Notes while learning to code in python

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