steveneale/ner_crf
Jupyter Notebook describing named entity recognition (NER) using conditional random fields (CRFs), implemented using scikit-learn / sklearn-crfsuite.
This project helps data scientists and NLP practitioners identify and categorize key entities like names, locations, or organizations within unstructured text. You provide raw text data, and it outputs a model that can automatically extract and label these specific pieces of information. It's designed for those who work with text analysis and need to pinpoint particular types of data within large volumes of content.
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Use this if you need to build a custom system to automatically extract specific types of information (like product names, dates, or job titles) from text documents.
Not ideal if you are not comfortable working with Python code and machine learning libraries, as this requires direct coding knowledge.
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Dec 07, 2018
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