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.
Fine Tune BERT for Text Classification with TensorFlow
Give your career the gift of Coursera Plus with $160 off, billed annually. Save today.
Fine Tune BERT for Text Classification with TensorFlow
Instructor: Snehan Kekre
17,185 already enrolled
Included with
Learn, practice, and apply job-ready skills with expert guidance
4.6
(200 reviews)
Intermediate level
Recommended experience
2.5 hours
Learn at your own pace
Hands-on learning
What you'll learn
Build TensorFlow Input Pipelines for Text Data with the tf.data API
Tokenize and Preprocess Text for BERT
Fine-tune BERT for text classification with TensorFlow 2 and TensorFlow Hub
Skills you'll practice
Details to know
Earn a career certificate
Add to your LinkedIn profile
Taught in English
No downloads or installation required
Only available on desktop
See how employees at top companies are mastering in-demand skills
Learn, practice, and apply job-ready skills in less than 2 hours
- Receive training from industry experts
- Gain hands-on experience solving real-world job tasks
- Build confidence using the latest tools and technologies
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:
Introduction to the Project
Setup your TensorFlow and Colab Runtime
Download and Import the Quora Insincere Questions Dataset
Create tf.data.Datasets for Training and Evaluation
Download a Pre-trained BERT Model from TensorFlow Hub
Tokenize and Preprocess Text for BERT
Wrap a Python Function into a TensorFlow op for Eager Execution
Create a TensorFlow Input Pipeline with tf.data
Add a Classification Head to the BERT hub.KerasLayer
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
8 project images
Instructor
Instructor ratings
4.7 (18 ratings)Offered by
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.
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Learner reviews
Showing 3 of 200
4.6
200 reviews
- 5 stars
71.28%
- 4 stars
20.29%
- 3 stars
4.45%
- 2 stars
1.48%
- 1 star
2.47%
You might also like
New to Machine Learning? Start here.
Open new doors with Coursera Plus
Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.
You can download and keep any of your created files from the Guided Project. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.