ELM classifier for detecting tuberculosis in lung X-rays

Homeworks of CMPE462 course in Bogazici University

A Java console application that implemetns k-fold-cross-validation system to check the accuracy of predicted ratings compared to the actual ratings.

Predicting Win/Loss/Draw on the Connect Four dataset with Tsetlin Machines

A Java console application that implemetns k-fold-cross-validation system to check the accuracy of predicted ratings compared to the actual ratings and RMSE to calculate the ideal k for our dataset.

An explainable and interpretable binary classification project to clean data, vectorize data, K-Fold cross validate and apply classification models. The model is made explainable by using LIME Explainers.

using Multi-Layer Perceptron (MLP) to analyze its different settings on the Iris and Glass identification datasets

Classify whether a transaction is fraudulent or not

Master's Thesis project at University of Agder, Spring 2020. Classification with Tsetlin Machine on board game 'GO'.

Machine Learning with MATLAB

Predicting house prices of the "California Housing" dataset.

As part of this project, various classification algorithms like SVM, Decision Trees and XGBoost was used to classify a GPU Run as high or low time consuming process. The main purpose of this project is to test and compare the predictive capabilities of different classification algorithms

Implementing Linear Regression for various degrees and computing RMSE with k fold cross validation, all from scratch in python.

The project provides a complete end-to-end workflow for building a binary classifier in Python to recognize the risk of housing loan default. It includes methods like automated feature engineering for connecting relational databases, comparison of different classifiers on imbalanced data, and hyperparameter tuning using Bayesian optimization.

Implementation of some classification and clustering methods

Ad campaign performance evaluation using AB Testing

This is software for the 10-fold validation of an CNN-based image-classification method.

Creating and visualising statistics from the results of k-fold validation.

Analyzing the HR Criteria of a Company and how they promote their Employees and keep Balance between them using Data Analytics, Data Visualizations, and Machine Learning Models for Classification Purposes.