Natural language processing

Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and natural-language tasks.

🚀 Feature request

In pipelines tests and documentation they are recurringly named nlp, the goal is to rename them to something more appropriate.

Motivation

nlp = pipeline(task='conversational', model='XXX')

This is a bit pre

@gojomo

Not a high-priority at all, but it'd be more sensible for such a tutorial/testing utility corpus to be implemented elsewhere - maybe under /test/ or some other data- or doc- related module – rather than in gensim.models.word2vec.

Originally posted by @gojomo in RaRe-Technologies/gensim#2939 (comment)

more details at: allenai/allennlp#2264 (comment)

Hi I would like to propose a better implementation for 'test_indices':

We can remove the unneeded np.array casting:

Cleaner/New:
test_indices = list(set(range(len(texts))) - set(train_indices))

Old:
test_indices = np.array(list(set(range(len(texts))) - set(train_indices)))

Natural language processing

Here are 12,722 public repositories matching this topic...

huggingface / transformers

🚀 Feature request

Motivation

apachecn / AiLearning

google-research / bert

hankcs / HanLP

explosion / spaCy

oxford-cs-deepnlp-2017 / lectures

virgili0 / Virgilio

RaRe-Technologies / gensim

keon / awesome-nlp

bharathgs / Awesome-pytorch-list

RasaHQ / rasa

chiphuyen / stanford-tensorflow-tutorials

flairNLP / flair

spencermountain / compromise

allenai / allennlp

nltk / nltk

botpress / botpress

hanxiao / bert-as-service

graykode / nlp-tutorial

stanfordnlp / CoreNLP

NLP-LOVE / ML-NLP

sloria / TextBlob

brightmart / text_classification

huggingface / datasets

crownpku / Awesome-Chinese-NLP

brightmart / nlp_chinese_corpus

nfmcclure / tensorflow_cookbook

NLPchina / ansj_seg

dragen1860 / TensorFlow-2.x-Tutorials

zihangdai / xlnet