This package features data-science related tasks for developing new recognizers for Presidio. It is used for the evaluation of the entire system, as well as for evaluating specific PII recognizers or PII detection models.
machine-learning
deep-learning
nlp
natural-language-processing
privacy
ner
transformers
pii
named-entity-recognition
spacy
flair
Обновлено 2024-11-22 01:17:04 +03:00
Context aware, pluggable and customizable data protection and de-identification SDK for text and images
hacktoberfest
microsoft
python
privacy
transformers
anonymization
anonymization-service
data-anonymization
data-loss-prevention
data-masking
data-protection
de-identification
dlp
pii
pii-anonymization
pii-anonymization-service
presidio
privacy-protection
text-anonymization
Обновлено 2024-11-22 00:54:06 +03:00
maximal update parametrization (µP)
Обновлено 2023-10-21 06:45:36 +03:00
[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining
deep-learning
natural-language-processing
representation-learning
transformers
language-model
natural-language-understanding
pretraining
contrastive-learning
pretrained-language-model
Обновлено 2023-07-25 17:21:55 +03:00
Japanese NLP sample codes
Обновлено 2021-10-19 17:45:33 +03:00
A relation-aware semantic parsing model from English to SQL
Обновлено 2021-06-19 03:42:00 +03:00