QuaXP – data quality explored

QuaXP – data quality explored

The project aims to raise or sharpen public awareness on data quality problems in the context of machine learning.

Targeting everyone, with or without prior knowledge in the area of computer science, the project implements two levels of difficulty: “beginner”, requiring neither background in machine learning nor coding skills, and “advanced”, for learners with basic coding skills. The goal of both is the exploration of the problems with data quality for machine learning, in several steps: assess the quality of the data, clean the data, observe the influence of the cleaning on the performance of the model.

Beiträge zu diesem Projekt:

SeaPiaC

SeaPiaC

The aim of the project is to create a digital collaborative learning environment in which students of TUHH and NCKU collaborate on challenges of sustainable nature-based coastal protection in times of a changing climate.

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