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https://github.com/johnsnowlabs/johnsnowlabs

Gateway into the John Snow Labs Ecosystem

https://github.com/johnsnowlabs/johnsnowlabs

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
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    Academic email domains
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (9.6%) to scientific vocabulary

Keywords

bert databricks gpt machine-learning natural-language-processing nlp python seq2seq spark t5
Last synced: 5 months ago · JSON representation

Repository

Gateway into the John Snow Labs Ecosystem

Basic Info
  • Host: GitHub
  • Owner: JohnSnowLabs
  • License: other
  • Language: Python
  • Default Branch: main
  • Homepage: https://nlp.johnsnowlabs.com
  • Size: 1.66 GB
Statistics
  • Stars: 70
  • Watchers: 17
  • Forks: 26
  • Open Issues: 10
  • Releases: 77
Topics
bert databricks gpt machine-learning natural-language-processing nlp python seq2seq spark t5
Created over 3 years ago · Last pushed 6 months ago
Metadata Files
Readme License

README.md

John Snow Labs: State-of-the-art NLP in Python

The John Snow Labs library provides a simple & unified Python API for delivering enterprise-grade natural language processing solutions: 1. 15,000+ free NLP models in 250+ languages in one line of code. Production-grade, Scalable, trainable, and 100% open-source. 2. Open-source libraries for Responsible AI (NLP Test), Explainable AI (NLP Display), and No-Code AI (NLP Lab). 3. 1,000+ healthcare NLP models and 1,000+ legal & finance NLP models with a John Snow Labs license subscription.

Homepage: https://www.johnsnowlabs.com/

Docs & Demos: https://nlp.johnsnowlabs.com/

Features

Powered by John Snow Labs Enterprise-Grade Ecosystem:

Installation

```python ! pip install johnsnowlabs

from johnsnowlabs import nlp nlp.load('emotion').predict('Wow that was easy!')

```

See the documentation for more details.

Usage

These are examples of getting things done with one line of code. See the General Concepts Documentation for building custom pipelines.

```python

Example of Named Entity Recognition

nlp.load('ner').predict("Dr. John Snow is an British physician born in 1813") ```

Returns :

| entities | entitiesclass | entitiesconfidence | |-----------|----------------|:--------------------| | John Snow | PERSON | 0.9746 | | British | NORP | 0.9928 | | 1813 | DATE | 0.5841 |

```python

Example of Question Answering

nlp.load('answer_question').predict("What is the capital of Paris") ```

Returns :

| text | answer | |-------------------------------|--------| | What is the capital of France | Paris |

```python

Example of Sentiment classification

nlp.load('sentiment').predict("Well this was easy!") ```

Returns :

| text | sentimentclass | sentimentconfidence | |---------------------|-----------------|:---------------------| | Well this was easy! | pos | 0.999901 |

python nlp.load('ner').viz('Bill goes to New York') Returns:
ner_viz_opensource For a full overview see the 1-liners Reference and the Workshop.

Use Licensed Products

To use John Snow Labs' paid products like Healthcare NLP, [Visual NLP], [Legal NLP], or [Finance NLP], get a license key and then call nlp.install() to use it:

```python ! pip install johnsnowlabs

Install paid libraries via a browser login to connect to your account

from johnsnowlabs import nlp nlp.install()

Start a licensed session

nlp.start() nlp.load('en.medner.oncologywip').predict("Woman is on chemotherapy, carboplatin 300 mg/m2.") ```

Usage

These are examples of getting things done with one line of code. See the General Concepts Documentation for building custom pipelines.

```python

visualize entity resolution ICD-10-CM codes

nlp.load('en.resolve.icd10cm.augmented') .viz('Patient with history of prior tobacco use, nausea, nose bleeding and chronic renal insufficiency.') ``` returns:
ner_viz_opensource

```python

Temporal Relationship Extraction&Visualization

nlp.load('relation.temporal_events')\ .viz('The patient developed cancer after a mercury poisoning in 1999 ') ``` returns: relationv_viz

Helpful Resources

Take a look at the official Johnsnowlabs page page: https://nlp.johnsnowlabs.com for user documentation and examples

| Resource | Description| |----------------------------------------------------------------------------------------------------------------------|-------------------------------------------| | General Concepts | General concepts in the Johnsnowlabs library | Overview of 1-liners | Most common used models and their results | Overview of 1-liners for healthcare | Most common used healthcare models and their results | Overview of all 1-liner Notebooks | 100+ tutorials on how to use the 1 liners on text datasets for various problems and from various sources like Twitter, Chinese News, Crypto News Headlines, Airline Traffic communication, Product review classifier training, | Connect with us on Slack | Problems, questions or suggestions? We have a very active and helpful community of over 2000+ AI enthusiasts putting Johnsnowlabs products to good use | Discussion Forum | More indepth discussion with the community? Post a thread in our discussion Forum | Github Issues | Report a bug | Custom Installation | Custom installations, Air-Gap mode and other alternatives
| The nlp.load(<Model>) function | Load any model or pipeline in one line of code | The nlp.load(<Model>).predict(data) function | Predict on Strings, List of Strings, Numpy Arrays, Pandas, Modin and Spark Dataframes | The nlp.load(<train.Model>).fit(data) function | Train a text classifier for 2-Class, N-Classes Multi-N-Classes, Named-Entitiy-Recognition or Parts of Speech Tagging | The nlp.load(<Model>).viz(data) function | Visualize the results of Word Embedding Similarity Matrix, Named Entity Recognizers, Dependency Trees & Parts of Speech, Entity Resolution,Entity Linking or Entity Status Assertion | The nlp.load(<Model>).viz_streamlit(data) function | Display an interactive GUI which lets you explore and test every model and feature in Johnsowlabs 1-liner repertoire in 1 click.

License

This library is licensed under the Apache 2.0 license. John Snow Labs' paid products are subject to this End User License Agreement.
By calling nlp.install() to add them to your environment, you agree to its terms and conditions.

Owner

  • Name: John Snow Labs
  • Login: JohnSnowLabs
  • Kind: organization

GitHub Events

Total
  • Create event: 304
  • Issues event: 8
  • Release event: 10
  • Watch event: 13
  • Delete event: 162
  • Member event: 2
  • Issue comment event: 37
  • Push event: 1,301
  • Pull request review comment event: 14
  • Pull request review event: 175
  • Pull request event: 630
  • Fork event: 7
Last Year
  • Create event: 304
  • Issues event: 8
  • Release event: 10
  • Watch event: 13
  • Delete event: 162
  • Member event: 2
  • Issue comment event: 37
  • Push event: 1,301
  • Pull request review comment event: 14
  • Pull request review event: 175
  • Pull request event: 630
  • Fork event: 7

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 30
  • Total pull requests: 1,484
  • Average time to close issues: 8 months
  • Average time to close pull requests: 6 days
  • Total issue authors: 19
  • Total pull request authors: 38
  • Average comments per issue: 1.23
  • Average comments per pull request: 0.05
  • Merged pull requests: 1,119
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 8
  • Pull requests: 814
  • Average time to close issues: 3 months
  • Average time to close pull requests: 2 days
  • Issue authors: 5
  • Pull request authors: 26
  • Average comments per issue: 0.38
  • Average comments per pull request: 0.03
  • Merged pull requests: 626
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • bugeki (4)
  • josejuanmartinez (4)
  • jsl-models (3)
  • dcecchini (2)
  • KshitizGIT (2)
  • gokhanturer (2)
  • franz101 (1)
  • diatrambitas (1)
  • mehmetbutgul (1)
  • eladitzhakian (1)
  • NSManogna (1)
  • solarosfitness (1)
  • Meryem1425 (1)
  • uzairahmadxy (1)
  • nogifeet (1)
Pull Request Authors
  • jsl-models (707)
  • C-K-Loan (86)
  • rpranab (77)
  • jsl-builder (72)
  • Cabir40 (67)
  • agsfer (61)
  • akrztrk (58)
  • gokhanturer (43)
  • Meryem1425 (41)
  • albertoandreottiATgmail (37)
  • KshitizGIT (33)
  • aymanechilah (30)
  • yigitgull (28)
  • diatrambitas (23)
  • dcecchini (18)
Top Labels
Issue Labels
new model (3) enhancement (2) question (2) bug (1)
Pull Request Labels
new model (705) Release (12) documentation (8) enhancement (6) bug (2) WIP (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 9,171 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 3
  • Total versions: 180
  • Total maintainers: 4
pypi.org: johnsnowlabs

The John Snow Labs Library gives you access to all of John Snow Labs Enterprise And Open Source products in an easy and simple manner. Access 10000+ state-of-the-art NLP and OCR models for Finance, Legal and Medical domains. Easily scalable to Spark Cluster

  • Versions: 180
  • Dependent Packages: 1
  • Dependent Repositories: 3
  • Downloads: 9,171 Last month
Rankings
Downloads: 2.5%
Dependent packages count: 4.8%
Average: 5.4%
Dependent repos count: 8.9%
Maintainers (4)
ckloan johnsnowlabs jslbot mehmetbutgul
Last synced: 6 months ago

Dependencies

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