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Fine Tune BERT for Text Classification with TensorFlow
Coursera Project Network

Fine Tune BERT for Text Classification with TensorFlow

Snehan Kekre

Instructor: Snehan Kekre

24,030 already enrolled

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Learn, practice, and apply job-ready skills with expert guidance
4.6

(201 reviews)

Intermediate level

Recommended experience

2.5 hours
Learn at your own pace
Hands-on learning
Learn, practice, and apply job-ready skills with expert guidance
4.6

(201 reviews)

Intermediate level

Recommended experience

2.5 hours
Learn at your own pace
Hands-on learning

What you'll learn

Details to know

Shareable certificate

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Taught in English
No downloads or installation required

Only available on desktop

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About this Guided Project

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introduction to the Project

  2. Setup your TensorFlow and Colab Runtime

  3. Download and Import the Quora Insincere Questions Dataset

  4. Create tf.data.Datasets for Training and Evaluation

  5. Download a Pre-trained BERT Model from TensorFlow Hub

  6. Tokenize and Preprocess Text for BERT

  7. Wrap a Python Function into a TensorFlow op for Eager Execution

  8. Create a TensorFlow Input Pipeline with tf.data

  9. Add a Classification Head to the BERT hub.KerasLayer

  10. Fine-Tune and Evaluate BERT for Text Classification

Recommended experience

It is assumed that are competent in Python programming and have prior experience with building deep learning NLP models with TensorFlow or Keras

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Instructor

Instructor ratings
4.7 (18 ratings)
Snehan Kekre
Coursera Project Network
11 Courses109,881 learners

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How you'll learn

  • Skill-based, hands-on learning

    Practice new skills by completing job-related tasks.

  • Expert guidance

    Follow along with pre-recorded videos from experts using a unique side-by-side interface.

  • No downloads or installation required

    Access the tools and resources you need in a pre-configured cloud workspace.

  • Available only on desktop

    This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.

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4.6

201 reviews

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