Neural Structured Learning, or NSL, in TensorFlow isn’t as complex as it sounds. Its a framework for training deep neural networks that rely on structured signals along with specific inputs. This learning model leverages Neural Graph Learning to accomplish training neural networks using graphs and structured data. These are generated by multiple sources such as knowledge graphs, medical records, genomic data, or multimodal relations. This also support the natural language processing used in the BERT algorithm.