Token Classification in NLP using spaCy

Overview

Delve into token classification in NLP with this focused learning path. This course centers on using spaCy for token classification, from setting up an NLP pipeline to advanced classification model fine-tuning. Upon completion, you'll be adept in utilizing spaCy for token classification in NLP.

Syllabus

Course 1: Building an NLP Pipeline with spaCy for Token Classification
Course 2: Linguistics for Token Classification in spaCy
Course 3: Practical Applications of spaCy for Real-Life Tasks

Courses

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3 hours
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Kickstart your journey into token classification by setting up an efficient NLP pipeline, learning about tokenization, POS tagging, and lemmatization with spaCy.
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3 hours
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Delve deeper into fully enhancing Token Classification by understanding linguistic and semantic aspects of Natural Language Processing. Gain grasp of language morphology and recognize entity types using spaCy.
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1 hour
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Understanding theory and basic tools of spaCy is of paramount importance, but applying them to real-life tasks is what drives value. The course focuses on four case studies that involve practical applications of spaCy to solve real-world problems.