Parameter management is essential for distributed training of large machine learning (ML) tasks.
Knowledge graph completion (a. k. a.~link prediction), i. e.,~the task of inferring missing information from knowledge graphs, is a widely used task in many applications, such as product recommendation and question answering.
Parameter servers (PSs) facilitate the implementation of distributed training for large machine learning tasks.
Thus, RDFFrames is a useful tool for data preparation that combines the usability of PyData with the flexibility and performance of RDF database systems.
Data, algorithms, and compute/storage infrastructure are key assets that drive data science and artificial intelligence applications.
The discrepancy results in sub-optimal and inefficient behavior by both the shipper and the airline resulting in the overall loss of potential revenue for the airline.