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Transfer Learning for NLP with TensorFlow Hub
  • Level Intermediate
  • Duration 2 hours
  • Course by Coursera Project Network
  • Offered by

About

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.

Modules

Transfer Learning for NLP with TensorFlow Hub

    • 1 Readings
    • 1 Plugin
    • 1 Lab
    • 1 Assignment
Show info about module content

1 Assignment

  • Graded Quiz: Test your Project Understanding

1 Labs

  • Transfer Learning for NLP with TensorFlow Hub

1 Readings

  • Project-based Course Overview

Auto Summary

Learn to leverage transfer learning for natural language processing with TensorFlow Hub in this hands-on project. Ideal for intermediate learners with Python and deep learning experience, you'll master using pre-trained NLP models, fine-tuning them on real-world data, and evaluating performance with Tensorboard. Offered by Coursera, the course spans 120 minutes and is available for free, primarily catering to learners in North America.

Snehan Kekre
Instructor

Snehan Kekre