This is the repository for the LinkedIn Learning course TensorFlow: Working with NLP. The full course is available from LinkedIn Learning.
TensorFlow 2.0 is quickly becoming one of the most popular deep learning frameworks and a must-have skill in your artificial intelligence toolkit. Using a hands-on approach, Jonathan Fernandes covers the key aspects of working with transformers in natural language processing, all in TensorFlow. He goes over the basics of working with text data, and explores transfer learning, fine-tuning BERT, and understanding the transformer model architecture. He also includes challenge/solution sets and assessment questions to help you optimize retention of the material.
This repository has branches for each of the videos in the course. You can use the branch pop up menu in github to switch to a specific branch and take a look at the course at that stage, or you can add /tree/BRANCH_NAME to the URL to go to the branch you want to access.
The branches are structured to correspond to the videos in the course. The naming convention is CHAPTER#_MOVIE#. As an example, the branch named 02_03 corresponds to the second chapter and the third video in that chapter.
Some branches will have a beginning and an end state. These are marked with the letters b for "beginning" and e for "end". The b branch contains the code as it is at the beginning of the movie. The e branch contains the code as it is at the end of the movie. The main branch holds the final state of the code when in the course.
When switching from one exercise files branch to the next after making changes to the files, you may get a message like this:
error: Your local changes to the following files would be overwritten by checkout: [files]
Please commit your changes or stash them before you switch branches.
Aborting
To resolve this issue:
Add changes to git using this command: git add .
Commit changes using this command: git commit -m "some message"
- To use these exercise files, you must have the following installed:
- You must have a Google account if you want to run any of the models.
- Clone this repository into your local machine using the terminal (Mac), CMD (Windows), or a GUI tool like SourceTree.
Jonathan Fernandes
Data Scientist
Check out my other courses on LinkedIn Learning.