Today machine learning is one of the most relevant information technologies. Among modern methods, supervised learning shows the highest practical applicability. However, it has significant limitations, including

• need for large samples of labeled data
• need for an expert designing learning pipelines
• insufficient inerpretability of learning results

AutoKE project is aimed at overcoming these limitations based on technologies:

• unsupervised learning
• automated machine learning
• ontology learning

Our tasks:

• development of software products and systems that democratize intelligent technologies
• obtaining fundamental theoretical results in the field of Computer Science and Artificail Intelligence

Examples of our research:

• automated clustering model selection for ontology learning

Contacts: Ildar Baimuratov, [email protected]