Token and Sentence Level Classification with Google's BERT (TensorFlow)
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Updated
Jul 11, 2019 - Python
Token and Sentence Level Classification with Google's BERT (TensorFlow)
BERT-Text-Features for Tokenized Transcripts from P2FA.
Exploited GoogleBERT embeddings on LIAR dataset for multi-class classification task of Fake news detection.
Code for replicating the results of "HateMonitors" at HASOC 2019
A Tensorflow LSTM spam detector utilizing GloVe word embeddings.
Implemented SOTA model for fine tuning our tweet and Reddit data for Prediction of Rumour through SDQC
Work for detecting toxicity across a diverse range of conversations
Knowledge Discovery using deep learning
Understanding Hugging Face's implementation of BERT and GPT2
Implementing Multilingual WSD using [Normal, Atten]BiLSTM, Seq2Seq[Atten], Multitask WSD
This project uses BERT(Bidirectional Encoder Representations from Transformers) for Yelp-5 fine-grained sentiment analysis. It also explores various custom loss functions for regression based approaches of fine-grained sentiment analysis.
A Docker container to act as a local runtime for Google Colab or private jupyter server with BERT preinstalled
Comparison of contextual (BERT) and uncontextual (GloVe and Word2Vec) word embeddings in the task of music genre classification from lyrics.
A showcase of combining Elasticsearch with BERT on the HackerNews public data
Detecting fake news articles by analyzing patterns in writing.
BERT semantic search engine for searching literature research papers for coronavirus covid-19 in google colab
Identify the Native Language of an Author using Neural Networks and BERT for vector representation.
Detect whether a tweet is for Real Disaster
Low resource machine translation using Transformers and Iterative Back translation
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