Knowledge Representation: Semantics and Data Structures

Related lectures (32)

Page 3 of 4

Explores RDF syntax, schema properties, and classification of resources in the Semantic Web.

Covers Spark Data Frames, distributed collections of data organized into named columns, and the benefits of using them over RDDs.

Explores Closed-Loop Lifecycle Management, Circular Economy, and Zero Defect Manufacturing strategies for sustainable development.

Introduces data modeling concepts, SQL usage, and Pandas library applications for efficient data processing.

Explores knowledge inference, embedding techniques, and schema matching in data integration.

Explores data wrangling with Hadoop, emphasizing storage formats and Hive for big data processing.

Explores the role of ontologies in neuroscience, focusing on organizing data and defining entity properties.

Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.

Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.