We recently held a hands-on, hybrid technical meeting in Paris dedicated to refining and optimizing the data and machine learning pipelines in SEDIMARK. The session brought together team members on-site and online to work through practical implementation details, address technical challenges, and identify improvements to enhance efficiency, interoperability, and security across the platform.
SEDIMARK knows the importance of regulating data management issues within a context such as the one posed by the project. A solution will be considered where consortium partners will deposit all underlying information on data-related business processes (data storage, data provisioning, processing etc.) of the SEDIMARK solution clearly and transparently. The purpose of the Data […]
Data quality is of the highest importance for companies to improve their decision-making systems and the efficiency of their products. In this current data-driven era, it is important to understand the effect that “dirty” or low-quality data can have on a business. Manual data cleaning is the common way to process data, accounting for more […]
The SEDIMARK project will be featured at Open Source Community Day 2025! Join us in Madrid on 23–24 September for this two-day event focused on boosting open source innovation through collaboration and community.
On June 25th and 26th, the SEDIMARK consortium gathered in Dublin, Ireland, for a new General Assembly meeting hosted by University College Dublin (UCD). The city’s vibrant atmosphere, combined with the university’s inspiring academic setting, offered the perfect environment for two intensive days of discussions, planning, and collaboration. The meeting focused primarily on the integration […]
As machine learning models grow in complexity, deploying them in real-world environments—especially on resource-constrained devices—requires a shift from “bigger is better” to “smaller and smarter.” One powerful method to achieve this is model pruning.
As the world becomes increasingly data-driven, the need for accurate and efficient forecasting methods has never been greater. Multivariate time series forecasting is a complex task that involves predicting future values based on multiple interrelated time series. Traditional methods often struggle to capture the intricate relationships between these series, leading to suboptimal predictions. This is where Crossformer comes in, and it works as a component inside the toolbox of SEDIMARK.
At the heart of #SEDIMARK lies a powerful AI architecture, featuring MageAI and MLFlow, designed to revolutionize energy optimization. MageAI orchestrates seamless AI workflows, while MLFlow automates robust machine learning pipelines, enabling accurate and localized energy consumption predictions. Our integrated system supports dynamic customer management strategies, ensuring a transparent, scalable, and efficient solution for energy […]
WINGS hosted a new face-to-face General Assembly meeting of the SEDIMARK project on March 19th and 20th in Athens, Greece. The mediterranean sea, a long and rich culture, excellent food, and wonderful people are always a winning formula. The whole consortium participated in the meeting, in which technical aspects regarding all of the active Work […]
