Open Source

3rd Oct, 2018

The Distiller

The Distiller poses an alternative solution for batch job execution for Data Science jobs with dependencies between scripts to existing systems like Apache Airflow or Luigi. That is mainly due to its local thinking when it comes to dependencies and input data, a modular and re-usable approach through stills, pipes, parameters and age requirements. Additionally, with features like data drivers and a built-in scheduler satisfying the age requirements, the complexity is reduced for the user. Apache Airflow and Luigi are developed over a longer time by more people and offer feature-rich systems. Especially components like a UI makes them easier to be monitored and controlled. Nevertheless, the Distiller has conceptual advantages, while the choice of which system to use is a matter of taste and personal preferences. The modularity allows the re-usage of code for different projects and makes it easier to collaborate with others to create pipelines of scripts and make use of existing ones. The age requirements and on-demand dependency exploration keeps the focus on the current work without the need to have the whole pipeline in mind.

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Data Science

29th Aug, 2018

Spotify Song Recommendations - ACM RecSysChallenge 2018

As part of the ACM RecSysChallenge 2018 in cooperation with Spotify, I created a recommendation system for music together with a co-student. We predict songs for different metadata and number of seed tracks using a combination of different approaches: Neighborhood-exploration, in combination with a latent feature representation for larger numbers of seed tracks and ranking of tracks based on an audio feature neural network. The neighborhood approach is an efficient way to generate good results, which can be improved inexpensively by matrix factorization and matching of audio features. With our approach, we reached a top 20% placement at the competition strictly meant for and restricted to academic participants.

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Open Source

8th Aug, 2016

fyrelab sentri

fyrelab sentri turns your Raspberry Pi into a extendable and fully configurable home monitoring system as a baby monitor, burglar alarm or pet watch. It uses additional hardware such as webcams, microphones, temperatures sensors etc. It is easily configurable through an included webtool and works with a event-condition-action logic configurable by the user.

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Software projects

2013-2015

Yoogo Vocabulary Trainer

Yoogo was a vocabulary trainer for iPhone and iPad built on the new iOS 7 interface at the time. It was built with Objective-C and had a variety of learning and testing mechanisms, learning reports, Dropbox sync, CSV import, etc.

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