spaCy
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What is spaCy?
spaCy is an open-source library for advanced Natural Language Processing (NLP) in Python. It's designed specifically for production use and helps you build applications that process and understand large volumes of text. Common use cases include information extraction, text classification, and sentiment analysis.
What other technologies are related to spaCy?
spaCy Competitor Technologies
NLTK
NLTK is another popular Python library for NLP, offering similar functionalities to spaCy, though generally considered less performant for production use.
CoreNLP
CoreNLP is a suite of NLP tools from Stanford, offering similar functionalities to spaCy, such as tokenization, parsing, and named entity recognition.
Stanford CoreNLP
Stanford CoreNLP is a suite of NLP tools from Stanford, offering similar functionalities to spaCy, such as tokenization, parsing, and named entity recognition.
OpenNLP
OpenNLP is another NLP toolkit that provides similar functionalities to spaCy, like tokenization, sentence segmentation, and named entity recognition.
TextBlob
TextBlob is a simpler NLP library compared to spaCy, offering basic functionalities for tasks like sentiment analysis and part-of-speech tagging.
Stanford NLP
Refers to the suite of NLP tools from Stanford, offering similar functionalities to spaCy, such as tokenization, parsing, and named entity recognition.
AllenNLP
No summary available
AllenNLP is a research library for building NLP models. While spaCy is designed for speed and production, AllenNLP is for research, but covers some of the same ground.
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spaCy Complementary Technologies
Gensim
Gensim is a library focused on topic modeling and document similarity, which complements spaCy's capabilities in areas like named entity recognition and dependency parsing.
HuggingFace
Hugging Face's Transformers library provides pre-trained models and tools that can be integrated with spaCy for advanced NLP tasks, especially leveraging transformer-based architectures.
BERT
BERT is a transformer-based model that can be used with spaCy to improve performance on various NLP tasks. spaCy can use BERT embeddings.
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Which job functions commonly mention spaCy?
Prompt Engineer
3.2% of all Prompt Engineer jobs mention spaCy
View 53
jobs on Sumble
AI Engineer
1.7% of all AI Engineer jobs mention spaCy
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jobs on Sumble
Machine Learning
1.6% of all Machine Learning jobs mention spaCy
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jobs on Sumble
Data Scientist
1.2% of all Data Scientist jobs mention spaCy
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jobs on Sumble
Data, Analytics & Machine Learning
0.4% of all Data, Analytics & Machine Learning jobs mention spaCy
View 6.3k
jobs on Sumble
Which organizations are mentioning spaCy?
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