A Bayesian Optimization Package with No Fuzz

Testing several hyperparameter optimization techniques.

I showcase that I have broad set of skills regarding machine learning algorithms since I use Logistic Regression, XGBoost and Neural Networks in this project. Especially that I have a good understanding regarding neural networks and the Keras library.

Finding the best solution for geometry of electrical devices based on defined target for frequency responses

A framework for exploring the condition space of free radical polymerization (FRP) using Bayesian optimization and Monte Carlo simulation

Different techniques to tune the hyperparameter of machine learning models.

Bayesian Optimization Algorithm for Molecular Conformers

Various small projects covering a wide range of topics

A submission for Garanti BBVA Teknoloji Data Science Challenge

An analysis of travel insurance policies

The project aims to identify the painter from the artwork through the use of CNN in fine tuning and from scratch

This repository contains an ML workflow to predict house prices in Ames, Iowa. This project work is carried out under the Machine Learning module of the GeoDSc track of the Copernicus Master in Digital Earth.

DataStorm is a DataScience Competition hold by OCTAVE, the John Keells Group. This is our 2nd time participating in this competition (we got to 5th place last year)

This code was created as part of a bachelor's thesis in the field of mathematics. It extends the BOIS for VQE algorithm by introducing "immediate sharing" and enabling sharing between geometries whose Hamiltonians are extended in differing sets of Pauli strings.

My undergraduate honours project, with others' private information/code removed.

Mind Foundry OPTaaS R Client

Bayesian Optimization for Machine Learning

Final Project about optimizing NN with Bayesian Optimization for Bayesian Methods in ML course in Washington University

Nathan Rumsey's junior year International Science and Engineering Fair (ISEF) Project for the 2019-2020 school year.

Team programming exercises for the course unit "Probabilistic Artificial Intelligence", ETH Zurich