How Knowledge Graphs Solve Machine Learning Problems

#artificialintelligence 

Data representation and data itself is the main prerequisite for a successful design and operation of a machine learning model. Data as the input of AI-based systems, such as input signals to a non-AI-based system, are typically correlated with other data elements. Incorrect data collection and representation similar to wrong feature extraction from data is why AI projects do not achieve a mature state as a product. A good example is the collected data from various sensors of an autonomous vehicle, which are related to one another in the time or space domain and whose analysis could help make a more precise prediction of possible events in AI components. A graph contains nodes connected by edges, and it is a visual representation of a network.

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