Applying deep learning on metadata data as a competitive accelerator KU Leuven
While data quality is an important issue in view of the developments in the area of data science. Reaping the benefits of artificial intelligence is impossible in the presence of data quality problems. Many data science projects need to start with a data cleaning phase, which at times can be very costly. A variety of data cleaning techniques exist, each targeted at different types of data quality problems. As manual data cleaning is costly, ...