Optimal Sparse Decision Trees

Wine Quality Classification Using Deep Learning

SchedMaster lies in its hybrid approach - combining classical scheduling algorithms with optimization techniques like Greedy Algorithms, Dynamic Programming, and Backtracking. Additionally, it leverages simple ML models to predict process behavior, detect anomalies in resource usage, and recommend the most suitable scheduling strategies.

Python project implementing Nearest Neighbor and Skyline Query Search algorithms with R-tree data structures for efficient spatial indexing. Part of COMP6210 group project at Macquarie University.

This project implements a specialized graph-based text analysis tool that creates paths between words and phrases based on their lengths. The algorithm can find word patterns in texts while handling inflected forms of words (particularly important for agglutinative languages like Hungarian).