Semantria vs SpaCy
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Detailed Comparison
Semantria applies Text and Sentiment Analysis to tweets, facebook posts, surveys, reviews or enterprise content. | It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages. |
Supports C++, Java, .Net, PHP, Python, Ruby, Javascript;Excel add-in installs and runs directly in your Microsoft Excel;Concept Matrix and Deep Learning;Content Discovery;Named Entity Extraction;Theme Extraction;Text Summarization;Query Categorization;Facets and Attributes;Crawling and Automatic Text Extraction;Wikipedia-based categorization technology | - |
Statistics | |
GitHub Stars - | GitHub Stars 32.8K |
GitHub Forks - | GitHub Forks 4.6K |
Stacks 1 | Stacks 220 |
Followers 11 | Followers 301 |
Votes 0 | Votes 14 |
Pros & Cons | |
No community feedback yet | Pros
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Integrations | |
| No integrations available | |
What are some alternatives to Semantria, SpaCy?
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MonkeyLearn
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Jina
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Sentence Transformers
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FastText
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CoreNLP
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Flair
Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS), sense disambiguation and classification.
Transformers
It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.
Gensim
It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.
