#自然语言处理#🦆 Contextually-keyed word vectors
#自然语言处理#Easy to use and understand multiple-choice question generation algorithm using T5 Transformers.
#自然语言处理#🦜 Containerized HTTP API for industrial-strength NLP via spaCy and sense2vec
#自然语言处理#A simple web application for searching Word2Vec embeddings derived from approximately 2,000 law reports published by the The Incorporated Council of Law Reporting for England & Wales (https://www.iclr...
#自然语言处理#This is a much more in-depth project of text classification using SpaCy, where Amazon food reviews dataset was used
What have Spacy's sense2vec 2019 word vectors learned from Reddit?
#自然语言处理#qlamda: txt2ques generation model
#自然语言处理#An end-to-end solution on how MCQs can be generated using T5 transformer model, word embeddings and decoding strategies
#自然语言处理#Neural Sense Embeddings, replicating "SENSEMBED: Learning Sense Embeddings for Word and Relational Similarity", Iacobacci, Pilehvar and Navigli, 2015