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Tidy up universe [ci skip]

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This commit is contained in:
Ines Montani 2019-06-02 12:38:48 +02:00
parent 638caba9b5
commit 42de5be90c
1 changed files with 9 additions and 14 deletions
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23
website/meta/universe.json
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@ -6,8 +6,7 @@
"slogan": "Python lib for exploring Deep NLP & NLU by Intel AI",
"github": "NervanaSystems/nlp-architect",
"pip": "nlp-architect",
"thumb": "https://raw.githubusercontent.com/NervanaSystems/nlp-architect/master/assets/nlp_architect_logo.png",
"code_example": [],
"thumb": "https://i.imgur.com/vMideRx.png",
"category": ["standalone", "research"],
"tags": ["pytorch"]
},
@ -17,7 +16,6 @@
"slogan": "Named-entity recognition using neural networks",
"github": "Franck-Dernoncourt/NeuroNER",
"pip": "pyneuroner[cpu]",
"thumb": "",
"code_example": [
"from neuroner import neuromodel",
"nn = neuromodel.NeuroNER(train_model=False, use_pretrained_model=True)"
@ -31,7 +29,6 @@
"slogan": "Natural Language Preprocessing Library in Health data",
"github": "NIHOPA/NLPre",
"pip": "nlpre",
"thumb": "",
"code_example": [
"from nlpre import titlecaps, dedash, identify_parenthetical_phrases",
"from nlpre import replace_acronyms, replace_from_dictionary",
@ -42,8 +39,7 @@
" text = f(text)",
"print(text)"
],
"category": ["standalone"],
"tags": []
"category": ["standalone"]
},
{
"id": "Chatterbot",
@ -51,7 +47,7 @@
"slogan": "A machine-learning based conversational dialog engine for creating chat bots",
"github": "gunthercox/ChatterBot",
"pip": "chatterbot",
"thumb": "https://chatterbot.readthedocs.io/en/stable/_images/banner.png",
"thumb": "https://i.imgur.com/eyAhwXk.jpg",
"code_example": [
"from chatterbot import ChatBot",
"from chatterbot.trainers import ListTrainer",
@ -91,15 +87,14 @@
"slogan": "Algorithms for monitoring and explaining machine learning models ",
"github": "SeldonIO/alibi",
"pip": "alibi",
"thumb": "https://docs.seldon.io/projects/alibi/en/v0.2.0/_static/Alibi_Logo.png",
"thumb": "https://i.imgur.com/YkzQHRp.png",
"code_example": [
">>> from alibi.explainers import AnchorTabular",
">>> explainer = AnchorTabular(predict_fn, feature_names)",
">>> explainer.fit(X_train)",
">>> explainer.explain(x)"
"from alibi.explainers import AnchorTabular",
"explainer = AnchorTabular(predict_fn, feature_names)",
"explainer.fit(X_train)",
"explainer.explain(x)"
],
"category": ["standalone", "research"],
"tags": []
"category": ["standalone", "research"]
},
{
"id": "spacymoji",