Natural Language Processing
46 learners
Linguistics for Token Classification in spaCy
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.
NLTK
Python
spaCy
5 lessons
21 practices
3 hours
Linguistics and Semantics
Lessons and practices
Filtering Syntactic Dependencies and Token Shapes
Filtering Specific Syntactic Dependencies and Token Shapes
Creating Sentence with Unique Dependency and Shape
Syntactic Dependencies and Token Shapes Filtering
Filtering Syntactic Dependencies and Numerically Initiated Token Shapes
Semantic Similarity with Custom Sentences
Semantic Similarity Between Two Specific Sentences
Semantic Similarity Between Unrelated Sentences
Finding the Most Dissimilar Sentences
Extracting Specific Morphological Features for Verbs
Extract Number Feature from Noun Tokens
Create a Sentence with Specific Morphological Features
Discovering Feature-Rich Sentence in Text Analysis
Filtering Out Organization Entities
Identifying Specific Entities in Custom Text
Extracting 'ORG' and 'GPE' Entities with Spacy
Unique Geopolitical Entities in Reuters Dataset
Modify Phonetic Key Function in spaCy
Implement Verb Count Pipeline Component
Creating a Vowel Detection Custom Extension in spaCy
Implement Same POS Counting Pipeline Component
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