Few-shot Named Entity Recognition | Decoding NLP Libraries (Concise Concepts)
#ner #nlp #spacy
In this video, we will understand in-detail the inner workings of few-shot named entity recognition algorithm where we train named entity recognition (NER) systems when a small number of in-domain labeled data is available using Concise Concepts python library. This video is part of "Decoding NLP Libraries" series, where the second library that we are decoding is python's concise concepts.
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⏩ IMPORTANT LINKS
Concise Concepts Github: https://github.com/Pandora-Intelligen...
Philip Vollet: / philipvollet
⏩ OUTLINE:
0:00 - Background and Example
03:13 - few shot NER code walkthrough - concise concepts python spacy
Watch some popular research papers in NLP: • Simple Unsupervised Keyphrase Extract...
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About Me:
I am Prakhar Mishra and this channel is my passion project. I am currently pursuing my MS (by research) in Data Science. I have an industry work-ex of 3 years in the field of Data Science and Machine Learning with a particular focus on Natural Language Processing (NLP).