Coursera Project Network
Fine Tune BERT for Text Classification with TensorFlow
Coursera Project Network

Fine Tune BERT for Text Classification with TensorFlow

Snehan Kekre

Instructor: Snehan Kekre

17,992 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.6

(206 reviews)

Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.6

(206 reviews)

Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

Details to know

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Assessments

1 assignment

Taught in English
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There is 1 module in this course

This is a guided project on fine-tuning a Bidirectional Transformers for Language Understanding (BERT) model for text classification with TensorFlow. In this 2.5 hour long project, you will learn to preprocess and tokenize data for BERT classification, build TensorFlow input pipelines for text data with the tf.data API, and train and evaluate a fine-tuned BERT model for text classification with TensorFlow 2 and TensorFlow Hub.

What's included

2 readings1 assignment1 ungraded lab1 plugin

Instructor

Instructor ratings
4.7 (19 ratings)
Snehan Kekre
Coursera Project Network
11 Courses115,170 learners

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4.6

206 reviews

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