MachineLearningSamples-BiomedicalEntityExtraction - MachineLearningSamples-BiomedicalEntityExtraction

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This real-world scenario focuses on how a large amount of unstructured unlabeled data corpus such as PubMed article abstracts can be analyzed to train a domain-specific word embedding model. Then the output embeddings are considered as automatically generated features to train a neural entity extraction model using Keras with TensorFlow deep learning framework as backend and a small amoht of labeled data.The detailed documentation for this scenario including the step-by-step walk-through: https://review.docs.microsoft.com/en-us/azure/machine-learning/preview/scenario-tdsp-biomedical-recognition.

https://github.com/Azure/MachineLearningSamples-BiomedicalEntityExtraction

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