This project is based on the Jupyter notebook gx-demo.ipynb
. It demonstrates the usage of the GX library for data testing
This project uses the GX library to perform various data analysis tasks. The gx-demo.ipynb
notebook contains step-by-step instructions and code snippets for using the library. It covers topics such as data loading, preprocessing, visualization, and model training.
This project requires Python and several Python libraries. The required libraries are listed in the requirements.txt
file. You can install them using pip:
pip install -r requirements.txt
- Set up GX context.
- Prepare data.
- Profile data (optional).
- Generate technical tests from profile.
- Add business tests.
- Create a checkpoint.
- Run the checkpoint on initial data.
- Load new data.
- Run the checkpoint on new data and build data docs.