Gallery — Recent

Thesis template for Bachelor's or Master's thesis, Faculty of Informatics and Statistics, University of Economics, Prague. Šablona pro bakalářské a diplomové prace, Fakulta informatiky a statistiky, Vysoká škola ekonomická v Praze.

We all have a good reason to learn a new language; discovering our roots, passion for travel, academic purposes, pure interest etc. However most of us find it hard to become conversationally fluent in a new language while we use traditional resources for learning like textbooks and tutorials on the internet. In this paper we propose a novel approach to learn a new language. We aim to develop an intelligent browser extension, LanGauger, that will help users learn foreign languages. This application will allow users to look up words while they are browsing, by highlighting the text to be learned. The application will then provide a translation of the word, its pronunciation and its usage context in sentences. In addition, this intelligent tutor will also remember what words have been seen by the user, and quiz them on these words at appropriate times. While testing the recall of the user, this feature will also allow users to frequently think about the language and use it.

Something I wrote up to help myself understand the Laplace Transform, what makes it so useful, and most importantly how to derive the Laplace Transform from those useful properties.

The XITS fonts provide a Times-like serif typeface for mathematical and scientific publishing. They provide a version of the STIX fonts enriched with the OpenType MATH extension, making them suitable for high quality mathematical typesetting with XeTeX and LuaTeX. XITS fonts are free and open source.

Homework template for my upper division math courses. Updated August 2019.

A template to make good looking conlang grammar books.

counting and probablity

This is template for ICDP conference http://www.icdp-conf.org/

In this work, we attempt to solve the Hit Song Science problem, which aims to predict which songs will become chart-topping hits. We constructed a dataset with approximately 1.8 million hit and non-hit songs and extracted their audio features using the Spotify Web API. We test four models on our dataset. Our best model was random forest, which was able to predict Billboard song success with 88% accuracy.