https://dasya.itu.dk/tags/python/ Recent content in Python on DASYA Hugo -- gohugo.io en-us © DASYA, IT University of Copenhagen Tue, 14 Jan 2025 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/osk-ecp-bench/ Tue, 14 Jan 2025 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/osk-ecp-bench/ The extended Cluster Pruning (eCP) index, is a hierarchical approximate nearest neighbor index. eCP-FS is a “white-box” implementation of the index as a file structure using zarr. The index building is done through Python, while the index loading and search have been implemented in both pure Python and a Rust-Python package. While the index is slower from disk than other disk-based ANN solutions due to it not being stored as a single or few binary files but tons of smaller files, it allows more control over what is loaded, is easy to extend and when in-memory is on par with other memory based indexes. 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/current/cities1/ Thu, 01 Jul 2021 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/cities1/ The idea behind “15-minutes cities” is that within a short walk or bike ride people should have access to all necessary facilities that constitute the essence of urban living, such as parks, shops, cafes, schools, hospitals. Initiatives to transform cities according to this paradigm are currently being implemented across the world, in an attempt to make urban spaces more liveable, sustainable and community-oriented. However, a systematic understanding of the connection between urban form and accessibility is missing. https://dasya.itu.dk/for-students/proposals/current/cycling/ Thu, 01 Jul 2021 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/cycling/ As a response to increased traffic congestion and the need to reduce carbon emissions, cities consider ways to modernise, build and extend transit systems. Transit network design solutions can benefit from analysing the large amount of crowd-sourced location data available, which provides valuable insights into population mobility needs. Designing efficient metro lines, bicycle paths, or bus routes brings a number of conflicting constraints into play: from the user’s perspective, an efficient transit network is easily accessible and time-efficient, while from the provider’s side there is, amongst others, a limitation on the budget. https://dasya.itu.dk/for-students/proposals/current/cities2/ Thu, 01 Jul 2021 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/cities2/ The idea behind “15-minutes cities” is that within a short walk or bike ride people should have access to all necessary facilities that constitute the essence of urban living, such as parks, shops, cafes, schools, hospitals. Initiatives to transform cities according to this paradigm are currently being implemented across the world, in an attempt to make urban spaces more liveable, sustainable and community-oriented. However, a systematic understanding of the connection between urban form and accessibility is missing. https://dasya.itu.dk/for-students/proposals/current/music_embeddings/ Thu, 01 Jul 2021 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/music_embeddings/ Musical genres are inherently ambiguous and difficult to define. Even more so is the task of establishing how genres relate to one another. Yet, genre is perhaps the most common and effective way of describing musical experience. The number of possible genre classifications (e.g. Spotify has over 4000 genre tags, LastFM over 500,000 tags) has made the idea of manually creating music taxonomies obsolete. The aim of this project is to create hyperbolic embeddings to learn a general music taxonomy based on the co-occurrence of genres. https://dasya.itu.dk/for-students/proposals/archive/wind_gnn/ Thu, 01 Jul 2021 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/wind_gnn/ The integration of wind power in the energy grid is dependent on accurate production forecasts. The power output curves between neighbouring wind farms are often correlated temporally and spatially, but currently, these spatiotemporal dependencies are under-utilised in prediction models. Graph neural networks allow for modelling these dependencies. In this project the student will implement a prediction model using a newly released Python library for temporal geometric graph neural networks in order to analyse dependencies across wind farms at different locations in Denmark. https://dasya.itu.dk/for-students/proposals/archive/automl-forecasting-energy/ Thu, 20 Aug 2020 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/automl-forecasting-energy/ With the recent hunger for being “data driven”, many organizations are eager for integrating ML in there decision making process. Unfortunately, competent data scientists are still relatively scarce, and manual model development cannot keep up with the demand for magic AI solutions. This is no less true when it comes to forecasting. Knowing the future is extremely handy when making decisions. AutoML for Time Series Forecasting Subsequently many systems are now developing and integrating AutoML tools for time series forecasting. https://dasya.itu.dk/for-students/proposals/archive/non-intrusive-load-monitoring/ Mon, 06 Jul 2020 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/non-intrusive-load-monitoring/ How much does our smart meter readings disclose about us? Can we disentangle the oven from the washing machine from the kettle? Can we identify demographics and behavior patterns from the stream of electricity data? Most danish homes are now equipped so-called “smart meters” - networked electricity meters that report consumption and load at much higher rate than conventional meters. Currently the meters report data back to a centralized datahub on an hourly basis, but the meters are capable of producing data at a much higher granularity than this.