Machine Learning and Semantic web are covering conceptually different sides of the same story - Semantic Web’s typical approach is top-down modeling of knowledge and proceeding down towards the data while Machine Learning is almost entirely data-driven bottom-up approach trying to discover the structure in the data and express it in the more abstract ways and rich knowledge formalisms. The talk will discuss possible interaction and usage of Machine Learning and Knowledge discovery for Semantic Web with emphases on ontology construction. In the second half of the talk we will take a look at some research using machine learning for Semantic Web and demos of the corresponding prototype systems.