IML4E
Industrial Machine Learning for Enterprises
Project description
Smart software solutions including AI and machine learning (ML) have shown a great potential to automate processes that were not accessible to automation. Since AI and ML differ from classical software development regarding fundamental activities and processes, it is unclear how AI and ML can be integrated into existing industrial-grade software development processes. Addressing the industrialisation of ML development and operations, the IML4E project will develop the IML4E framework, covering methods, techniques and tools dedicated to deliver and maintain high-quality smart software in efficient, scalable and manageable processes.
https://iml4e.org
Finland
Basware Oy
Finland
Granlund Oy
Finland
Reaktor Innovations
Finland
Silo AI
Finland
University of Helsinki
Finland
Germany
Hungary
University of Debrecen
Hungary
Vitarex Studio Ltd
Hungary
Project publications
- IML4E Project profile leaflet Project Leaflet 24 May 2022 Download
- ITEA PO Days 2023 - Project poster IML4E Project poster 14 September 2023
- Influencing Europeans Software Innovations Press article 23 August 2022
Work package documents
- IML4E-D2.1-V1.0-Baseline methods and techniques for data collection, processing, and valorisation.pdf Work package document 31 January 2022
- IML4E-D2.2-V1.0-First version of methods and techniques for data collection, processing, and valorisation.pdf Work package document 02 June 2022
- IML4E-D2.3-V1.0-First version of tools for data collection, processing, and valorisation.pdf Work package document 05 December 2022
- IML4E-D3.1-V1.0-Baseline methods and techniques for advanced model engineering.pdf Work package document 04 February 2022
- IML4E-D3.2-V1.0-First version of methods and techniques for advanced model engineering.pdf Work package document 13 June 2022
- IML4E-D3.3-V1.0-First version of tools for advanced model engineering.pdf Work package document 14 December 2022
- IML4E-D4.1-V1.0-Requirements for the IML4E online experimentation and training platform.pdf Work package document 27 June 2022
- IML4E-D4.2-Initial MLOps methodology and the architecture of the IML4E framework.pdf Work package document 25 January 2023