TypeScript vs. JavaScript: A Guide
September 30, 2024
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Instructor: Snehan Kekre
17,703 already enrolled
Included with
(203 reviews)
Recommended experience
Intermediate level
It is assumed that are competent in Python programming and have prior experience with building deep learning NLP models with TensorFlow or Keras
(203 reviews)
Recommended experience
Intermediate level
It is assumed that are competent in Python programming and have prior experience with building deep learning NLP models with TensorFlow or Keras
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
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Only available on desktop
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.
Prerequisites: In order to successfully complete this project, you should be competent in the Python programming language, be familiar with deep learning for Natural Language Processing (NLP), and have trained models with TensorFlow or and its Keras API. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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
It is assumed that are competent in Python programming and have prior experience with building deep learning NLP models with TensorFlow or Keras
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
The Coursera Project Network is a select group of instructors who have demonstrated expertise in specific tools or skills through their industry experience or academic backgrounds in the topics of their projects. If you're interested in becoming a project instructor and creating Guided Projects to help millions of learners around the world, please apply today at teach.coursera.org.
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.
203 reviews
71.21%
20.48%
4.39%
1.46%
2.43%
Showing 3 of 203
Reviewed on Dec 14, 2020
Great course. Easy to follow & straightforward explanations.
Reviewed on Feb 1, 2023
it is very helpful and simply explain the idea of Bert model , really it is useful project
Reviewed on Jun 19, 2021
The project is very clear and easy to follow. Would suggest providing some gmail account so that we don't have to log into the colab using our own google credentials.
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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.
At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.