https://dasya.itu.dk/tags/data-analysis/ Recent content in data analysis on DASYA Hugo -- gohugo.io en-us © DASYA, IT University of Copenhagen Fri, 22 Nov 2024 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/vs-similarity/ Fri, 22 Nov 2024 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/vs-similarity/ Machine learning methods are often evaluated on benchmark datasets, in computer vision, medical imaging, NLP and other fields. In such evaluation, researchers often describe the data as being: representative, for example based on the distribution of ages of the patients mirroring the world population, similar, for example because both dataset contain pictures of animals diverse, for example because data was collected from multiple countries Recent research shows, the concepts of representativity, similarity, and diversity, are not strictly defined, and different notions might be used by different researchers. https://dasya.itu.dk/for-students/proposals/archive/timeseriesanalysis/ Wed, 09 Feb 2022 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/timeseriesanalysis/ Outlier detection is carried out when the information is stored at the server. However, with the new IoT computational capabilities, outlier detection can be developed locally. Therefore, it is necessary to know how much RAM/Flash is needed for this step and which IoT brands can handle it. This project is divided into two parts. The first is implementing light-heavy ML algorithms in single points with few instances. Second, deploy the outlier detection to implement deep learning techniques related to time series analysis. https://dasya.itu.dk/for-students/proposals/archive/tinyml/ Wed, 09 Feb 2022 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/tinyml/ TinyML is a new trend to deploy deep learning in tiny devices. Therefore, it is necessary to deploy several applications to understand the challenges and opportunities which tinyML brings us. In this scenario, any idea with embedded computer vision, voice recognition, and sensors are welcome. https://dasya.itu.dk/for-students/proposals/archive/wind-turbine-electricity-production-analysis/ Mon, 16 Dec 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/wind-turbine-electricity-production-analysis/ Energinet has a model that describes the electricity production of a given wind turbine given wind conditions. The current model based on kNN is trained with DMI weather data and historical electricity production data for the wind turbine. The goal of the project is to improve the current model with lifelong learning, extended weather data and different models for a range of different wind turbines. Testing models in reverse, it should also be possible to derive wind conditions from a turbine’s electricity production.