Sentiment Analysis | BERT tutorial | Transformer | TensorFlow Keras Python | Text Classification NLP

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The BERT framework, a new language representation model from Google AI, uses pre-training and fine-tuning to create state-of-the-art models for a wide range of tasks. These tasks include question answering systems, sentiment analysis, and language inference.

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UnparsedFlagAccessError: Trying to access flag --preserve_unused_tokens before flags were parsed. How can I solve it ?

jayasuryav

thank you for the video. Can you please provide me the code.

ummarafatima

Hallo Sir, Thank you for the tutorial, How do I make the prediction on the test set with several other metrics such as AUC. Usually we use scikit-learn.metrics to do that. I tried y_hat=model.predict(test_data), but where is the y_test. Thank you for your answer.

rickymaulanafajri

How this can be used in news classification in nepali language.

prakashkafle

Which BERT model have you implemented here?

hritiknandanwar

can you please send me the source code?

Kupgnd

Thank you so much, I need this code please.

hanaaaliabedal_shibani

thank you sir for the explaination can you please provide me the code.

susmitamajumder

can BERT used in arabic with arabic language? thank for this video

Aliabbashassan

Can we see a deployment of this model using flask.

shashanksingh

@
Tattvamasi sir can i get the source please, i sent you an email

malekferchichi

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