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ZenML 🙏: The bridge between ML and Ops. https://zenml.io.
## Describe changes This PR fixes some smaller issues: - Allows custom materializers in step operators - Prevents nested pipeline execution - Fixes the tf dataset materializer to work with...
## Describe changes I implemented/fixed _ to achieve _. ## Pre-requisites Please ensure you have done the following: - [X] I have read the **CONTRIBUTING.md** document. - [ ] If...
## Describe changes Added ignored_columns to Evidently StandardStep to filter dataframe columns, to enable drift detection on selected columns. - This fixes the **(Issue : #600 )** ## Pre-requisites Please...
I ported a version of our Pillow image materializer from the annotation example such that it works with #812. ## Pre-requisites Please ensure you have done the following: - [x]...
## Describe changes This PR implements a generic way to reference secrets for (most) stack component attributes. Instead of passing in the attribute value directly, stack component attributes now allow...
### Contact Details [Optional] [email protected] ### System Information ZenML version: 0.11.0 Install path: /media/alaridl/DATA_LINUX1/pypoetry/virtualenvs/zenmlenv-Rn-xthbg-py3.9/lib/python3.9/site-packages/zenml Python version: 3.9.13 Platform information: {'os': 'linux', 'linux_distro': 'ubuntu', 'linux_distro_like': 'debian', 'linux_distro_version': '20.04'} Environment: native Integrations:...
## Describe changes This PR greatly increases the flexibility in which users can specify how ZenML builds the Docker image that is used to run their pipeline steps in remote...
## Describe changes I implemented/fixed _ to achieve _. - Adjusted the quickstart example to use tabular data (iris flower classification) - Modified FacetsVisualizer to be able to directly take...
## Describe changes I revamped `materializers.built_in_materializer.py` to add support for `bytes`, `set`, and non-JSON-serializable `dict`, `list`, and `tuple` objects. The main implication of this is that you can now use...
Hey everyone and welcome to the long-awaited Spark PR. With this PR, we go over a new integration with ZenML and you can think of it as our first steps...
