Transfer Learning for NLP with TensorFlow Hub

115 ratings
Offered By
Coursera Project Network
4,134 already enrolled
In this Free Guided Project, you will:

Use pre-trained NLP text embedding models from TensorFlow Hub

Perform transfer learning to fine-tune models on real-world text data

Visualize model performance metrics with TensorBoard

Showcase this hands-on experience in an interview

Clock1.5 hours
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

This is a hands-on project on transfer learning for natural language processing with TensorFlow and TF Hub. By the time you complete this project, you will be able to use pre-trained NLP text embedding models from TensorFlow Hub, perform transfer learning to fine-tune models on real-world data, build and evaluate multiple models for text classification with TensorFlow, and visualize model performance metrics with Tensorboard. 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.


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

Skills you will develop

  • Natural Language Processing
  • Deep Learning
  • Inductive Transfer
  • Machine Learning
  • Tensorflow

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 and Project Overview

  2. Setup your TensorFlow and Colab GPU Runtime

  3. Download and Import the Quora Insincere Questions Dataset

  4. TensorFlow Hub for Natural Language Processing

  5. Define Function to Build Models

  6. Compile Models

  7. Train Various Text Classification Models

  8. Compare Accuracy and Loss Curves

  9. Fine-tune Model from TF Hub

  10. Train Bigger Models and Visualize Metrics with TensorBoard

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step



View all reviews

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.