High performance algorithms in C#: SIMD/SSE, multi-core and faster
This is a web-based app that I developed with Dash framework and Python in 2021 as a course project in the Artificial Intelligence Graduate Program at the University of San Diego. The objective is to use the dataset from diabetes labs to train a Machine Learning model to predict diabetes based on diagnostic measurements.
Track and compare performance of all methods tested on Bench2Drive, presenting a clear view of autonomous driving benchmarks and their results.
This is a repository of the code used for the experimental work in my Bachelor thesis on Approximation Algorithms for Graph Edit Distance (GED). It includes implementations, benchmarking scripts, and evaluation methods for comparing GED approximation algorithms with exact computations.
Research materials for reproducibility purposes.
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