tools for scalable and non-intrusive parameter estimation, uncertainty analysis and sensitivity analysis

User documentation website for the Sulis tier 2 HPC service. Built using Jekyll.

A collection of AI and ML projects demonstrating various techniques, algorithms, and applications.

My Final Project for my Introduction to Data Science course at Simmons University.

This is an assignment from my Machine Learning for Mechanical Engineers course that demonstrates an understanding in decision trees and ensemble methods using scikit-learn.

This repository hosts the Cervical Cancer Image Classification project, a comprehensive effort aimed at improving the classification accuracy of Squamous Cell Carcinoma (SCC) through advanced deep learning models and ensemble techniques. The project utilizes the Herlev dataset.

Time series forecasting with Fourier-adjusted time dummies

[ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架

Projects completed as a part of IIIT-Delhi's Post Graduation Diploma in Computer Science and Artificial Intelligence.

Comparison of ensemble learning methods on diabetes disease classification with various datasets

Instructional materials (course files) for the BBT4206 course (Business Intelligence II) using R. Topic: Ensemble Methods.

Using deep learning to predict whether students can correctly answer diagnostic questions

The goal of this report was to identify which variable best predicts divorce using decision trees and other ensemble methods. In the data set, Class is the response variable, with 0 = still married and 1 = divorced.

Predict sale prices via regression models, using PCA, k-means clustering, ensemble models, pipelines, etc.

Course project for Stanford's STATS 315B (Modern Applied Statistics: Learning II).

Diabetes prediction using bagging (ensemble methods)

Build a classification model to predict clients who are likely to default on their loans. Give recommendations to the bank on important features to consider while approving a loan. Concepts Used: Logistic Regression, Decision Trees, Random Forests, and Ensemble Methods

Identification of Lung Cancer in Smoker Person Using Ensemble Methods Based on Gene Expression Data. Presented in IC2IE and published to IEEE.

AI-CryptoTrader is a state-of-the-art cryptocurrency trading bot that uses ensemble methods to make trading decisions based on multiple sophisticated algorithms. Built with the latest machine learning and data science techniques, AI-CryptoTrader provides a powerful toolset and advanced trading stratgies for maximizing your cryptocurrency profits.

This project presents a ML based solution using Ensemble methods to predict which visa applications will be approved and thus recommend a suitable profile for applicants whose visa have a high chance of approval