The difference between graph neural networks and standard machine learning models is that they take into account all relationships in the data, making them more flexible and adaptable. For example, in chatbots, each word is analyzed in the context of previous words, which allows more accurate answers to be obtained.
MTS Big Data Center Director Viktor Kantor noted that this library will help reduce the complexity of creating graphical neural networks. It combines well-known deep learning models and provides a tool for new research.
Opening the Coolgraph source code encourages talented people to try this technology in the field of machine learning.
Source: Ferra
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