Want to hire Spacy developer? Then you should know!
How and where is Spacy used?
- Natural Language Processing: Text summarization
- Named Entity Recognition: Entity extraction
- Part-of-Speech Tagging: Grammar analysis
- Dependency Parsing: Syntactic parsing
- Text Classification: Sentiment analysis
- Tokenization: Breaking text into tokens
- Entity Linking: Linking entities to a knowledge base
- Word Vector Representations: Text similarity
- Text Clustering: Grouping similar documents
- Relation Extraction: Identifying relationships between entities
Compare Junior, Middle, Senior, and Expert/Team Lead Spacy Developer roles
Seniority Name | Years of experience | Responsibilities and activities | Average salary (USD/year) |
---|---|---|---|
Junior | 0-2 years |
| $60,000 |
Middle | 2-4 years |
| $80,000 |
Senior | 4-6 years |
| $100,000 |
Expert/Team Lead | 6+ years |
| $120,000 |
Quick Facts about Spacy.
- Spacy was created in 2015 by Explosion AI, offering fast NLP processing.
- It is commonly used in projects involving text classification and information extraction.
- The entry threshold for using Spacy is relatively low due to its user-friendly API.
- One of the most popular related technologies to Spacy is the Natural Language Toolkit (NLTK).
- Fun fact: Spacy’s tagline is “Industrial-strength natural language processing.”
TOP Spacy Related Technologies
- Python 3.7
- Cython (Stefan, 2007)
- Numpy (Travis, 2006)
- Scipy (Travis, 2001)
- Sklearn (Pedregosa, 2011)
What are top Spacy instruments and tools?
- Spacy: Industrial-strength natural language processing.
- Thinc: Deep learning library for NLP.
- Thinc-Comp: Library for computational semantics.
- Prodigy: Active learning tool for data annotation.
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