| Developers: | Innodata |
| Date of the premiere of the system: | 2023/12/11 |
| Technology: | Data Quality |
Main Article: Data Quality Management
2023: Registration in Rospatent
The company Innodata"" registered Rospatent in ML Fab -D/MLOps-platform, which combines quality management tools data and tools for automating the life cycle of models. machine learning The company announced this on December 11, 2023.
The ML Fab D/MLOps platform is designed to manage the lifecycle of machine learning models and data for them. The product can be used by any organization developing and operating machine learning models and services based on them. Integrated with the ML model development environment, Data Governance enables Data Science and business analysts to quickly find the data they need and share analysis results, significantly improving model quality and accelerating project implementation.
The capabilities of ML Fab are provided by the functionality of many Open Source components that are used to create data pipelines, store and version datacets, create and test machine learning models, create and publish web services based on them, monitor published services, visualize model quality metrics, store and version model code, as well as experiment on their training.
The platform is deployed in the Kubernetes software environment using authoring code that installs and configures all the necessary platform components from a single repository. Platform users are accessed through a web browser.
 | This is not the first year we have been introducing popular solutions in the field of data management and machine learning, "said Alexander Sergienko, executive director of Innodat. Registration of the ML Fab platform in Rospatent is another important stage for this area of activity of our company and strengthening its position in the market of domestic developers of innovative digital products. Within the framework of current and future projects, we plan to adapt the universal functionality of the solution to the needs and business processes of our customers from various industries, including transport, retail and industry. |  |
| The site content is translated by machine translation software powered by PROMT. The machine-translated articles are not always perfect and may contain errors in vocabulary, syntax or grammar. Read original article If you find inaccuracies or errors in the results of machine translation, please write to editor@tadviser.ru. We will make every effort to correct them as soon as possible. |