Explanatory Model Analysis. Explore, Explain and Examine Predictive Models

Use AutoAI to detect fraud

Official implementation of the paper *PDE-Driven Spatiotemporal Disentanglement*

we proposed a software defect predictive development models using machine learning techniques that can enable the software to continue its projected task.

Machine learning to predict future number Covid19 Daily Cases (7-day moving average). Long Short Term Memory (LSTM) Predictor and Reinforcement Learning (RL) Prescription with Oxford Dataset

Portfolio of course work for my Master's in Data Science.

Supporting code for https://www.biorxiv.org/content/10.1101/796714v4

Plotly Dash HTML Python Flask site for user to interact with a trained machine learning model to predict the round-trip cost of flights — based on 9 million 2018 Domestic Flight Prices in the United States.

Machine Learning Introductory Course

Course Project for UCSD ECE143: Programming for Data Analytics

No description provided.

Recurrent Dynamic Graph Mapper using GNN

Our Economic Forecasting Model leverages Genetic Algorithms and Random Forests to provide farmers, policymakers, and businesses with cutting-edge insights for informed, profitable decisions in the ever-changing world of agriculture.

Mix of good tools for portfolio analysis

Reproduce Predictive Models of Fire via Deep learning Exploiting Colorific Variation (ICAIIC2019) with Pytorch

Trabajo de Fin de Grado del Grado de Ingeniería Informática, realizado en la Escuela Técnica Superior de Ingeniería Informática de la Universidad Politécnica de Madrid.

This project aims to analyze trends in the Paycheck Protection Program and to generate predictive models based on demographics to predict the likelihood of receiving a loan.

A few-shot learning approach to forecasting the evolution of the brain connectome.

Statistical analysis of animal shelter intakes and outcomes from Dallas Animal Services, and a fullstack app for predicting animal outcomes based on intake variables.

PRESS: Predictive State Smoothing in Python (tf.keras)

This repository contains code for predicting the price of mobile phones using regression models. It includes the implementation of various regression techniques such as Random Forest Regression, Decision Tree Regressor, Linear Regression, and Lasso Regression.

A lightweight agentic‑AI workflow built in n8n to help a rural GP clinic automatically triage patient feedback. Using LLM‑based classification, structured routing, and human oversight, it categorizes feedback, assesses risk, and notifies the right provider—supporting safety and communication in resource‑limited settings.

Simulation of the 2026 FIFA World Cup using a Monte Carlo approach, combining historical achievements, FIFA rankings, team form, and modern football tactics. The model explores which teams are best adapted to modern tournament football under extreme variance, giving insights into favorites and potential dark horses.

This project explores linear regression model selection in R using Best Subset Selection (BIC), stepwise methods with cross-validation, Ridge, and Lasso. Includes MSE evaluation on test data, multicollinearity analysis (VIF), and correlation insights for variable selection.

This repository contains coursework for the Business Analytics Foundations course in the MS Applied Business Analytics program at Boston University.

A web-based application that predicts multiple diseases including diabetes, heart disease, stroke, chronic kidney disease, and liver disease using machine learning models. The system leverages optimized ML algorithms to provide accurate predictions and offers a user-friendly interface for input and result visualization.

An explainable inductive learning model on gene regulatory and toxicogenomic knowledge graph (under development...)

🔧 Control stepper motors wirelessly with VAL3000, the quick and easy driver that requires no programming. Perfect for precise motor management.

Contains implementations of Classical and widely used machine learning algorithms right from begining

This is a machine learning project that predicts the value of a house based on its feature inputs.