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MLRun template functions and examples
Run data validation via Great Expectations. Will validate a given dataset with a given set of expectations, run the validation, and log the output HTML data doc in MLRun.
This function is set to work in 0.10.1 for various bug fixes in progress, hence submission to dev branch only.
I was going through the tf2_serving_v2 notebook and i noticed that methods that were mentioned in text cell above were actually from tf2_serving notebook. It led to some confusion in...
1. tar.gz and zip files quite often contain nested archives. `tarfile` recursively extracts files, `zipfile` doesn't and requires an extra step. This leaves the artifact contents incompletely extracted. 2. In...
**[describe](https://github.com/mlrun/functions/blob/development/describe/describe.ipynb)** is slow for the most part due to seaborn `pairplot`. The seaborn sourcecode has a **[comment](https://github.com/mwaskom/seaborn/blob/2d3502b05d91343bd37d8f8074874cfbae9f1e68/seaborn/axisgrid.py#L1358)** suggesting plot set-up is the time-consuming part. Needed is a new parameter that...
Each function should have its own README file describing the correct usage, options and provide use cases
none of the dask functions have been tested in this new repo
Hi @guy1992l @ZeevRispler @yonishelach I have followed your work of auto_trainer to implement the dpo trainer. Please review and let me know. Thanks
Bumps [scikit-learn](https://github.com/scikit-learn/scikit-learn) from 1.0.2 to 1.5.0. Release notes Sourced from scikit-learn's releases. Scikit-learn 1.5.0 We're happy to announce the 1.5.0 release. You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_5_0.html and...
Added model server to deploy models trained with mlflow and tracked by mlrun.