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John Snow Labs - NLP Libraries

John Snow Labs Inc

John Snow Labs - NLP Libraries

John Snow Labs Inc

NLP & OCR libraries, models and notebooks for text and image annotation and model training & tuning

About the offer

This product includes the entire suite of Natural Language Processing Python libraries by John Snow Labs. It allows quick and easy text annotation with pre-trained DL models and rules but also NLP model testing, training and tuning. The product guarantees state-of-the-art accuracy, native scalability, optimizations for the latest hardware, and the ability to easily compose text and image processing pipelines.

There is no limit on the number of documents, models, or pipelines that can be used with this subscription: the software is licensed on a per-server basis.

What is included

  • Spark NLP, the most widely used NLP library in the Enterprise. It provides production-grade, scalable, and trainable versions of the latest research in natural language processing and 10,000+ pre-trained models and pipelines covering tasks such as Entity Recognition, Information Extraction, Spelling and Grammar, Text Classification, Translation, Summarization, Question Answering or Emotion Detection.
  • Healthcare NLP software and models, enabling clinical and biomedical Named Entity Recognition for 400+ entity types, assertion status detection (identify between positive, negative, possible, past, and future facts), clinical relation extraction, clinical entity resolution to SNOMED-CT, ICD-10, CPT, RxNorm, LOINC, NDC, ICD-I, MeSH, UMLS.
  • Finance NLP software and models, enabling financial Named Entity Recognition (e.g. organizations, products, revenue, profit, losses, trading symbols, etc.), Entity-linking for normalizing NER entities and linking them to databases such as Edgar, Crunchbase, and Nasdaq, Assertion Status for inferring temporality and Relation Extraction.
  • Legal NLP software and models, covering Named Entity Recognition, Entity-Linking, Assertion Status and Relation Extraction. It includes access to over 300+ new state-of-the-art models available in multiple languages.
  • Visual NLP (OCR) software and models, enabling form understanding, table detection and extraction, noisy image enhancement, visual document classification, visual entity recognition, signature detection, and image de-identification.
  • Full access to all models and pipelines published on the NLP Models Hub (currently 12,500+ and counting).
  • 30+ Ready-to-use Jupyter notebooks that will help you get started with text and image analysis on all major NLP tasks such as text classification, sentiment analysis, named entity recognition, relation extraction, assertion status, entity linking, de-identification, translation, summarization, question answering, spelling and grammar.
  • NLU python library for text understanding that can be used to test models and pipelines with one line of code.
  • Spark NLP Display library for out-of-the-box annotation display on top of textual content.

Who is this offer for

  • Teams of python developers that need to extract entities and relations from text, image and pdf documents;
  • Data scientists who deal with NLP problems;
  • Machine learning engineers who need to test/train/tune NLP models;
  • Scientific researcher groups who need to extract meaning from unstructured, natural language documents;
  • Anyone else interested in text and image analysis, image digitization, data extraction, document labeling and/or NLP model training.

Target verticals

The NLP libraries included in this offer are general, can be applied to any domain and to documents written in over 250 languages. The NLP Models Hub contains over 12k pre-trained models and pipelines for general-purpose documents. It also contains specialized pre-trained models for the following verticals:

  • Healthcare
  • Finance
  • Legal

Technical Specifications

  • Recommended memory: 32GB RAM
  • Recommended vCPU:8 vCPUs
  • Operating System:Ubuntu 20.04

Included integrations

  • Jupyter notebook; preinstalled and running on port 5000.

3 Easy Steps to get started

  1. Subscribe to the product on the Azure Marketplace.
  2. Deploy it on a new machine.
  3. Access the welcome page for a guided experience on http://instanceIP
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