We currently use pylint 2.11.1. This is a bit old so we should upgrade it to the latest version (2.14.4):

https://github.com/mlflow/mlflow/blob/d40780be361f4bd2741c2e8fcbd428c1d693edcf/requirements/lint-requirements.txt#L1

• https://pypi.org/project/pylint/2.11.1/
• https://pypi.org/project/pylint/2.14.4/

Is there an existing integration?

• I have searched the existing integrations.

Use Case

This will allow to host the software on a serverless and stateless service. This will facilitate scaling because no critical data will be on the disk of the system running the application.

Motivation

Allow users to save resources and money.

Implementation

No response

Anything e

We currently have read and write capabilities but do not support deleting. We could add a few calls like delete delete_all and some recursive way of deleting.

🚨🚨 Feature Request

• A new implementation (Improvement, Extension)

Is your feature request related to a problem?

Currently, if a user tries to access an index that is larger than the dataset length or tensor length, an internal error is thrown which is not easy to understand.

Description of the possible solution

We can catch the error and throw a more descriptive e

Is your feature request related to a problem? Please describe.

Feast is often hard to install alongside other python packages that use google-cloud-core. Specifically, Feast sets an upper-bound on this library (2.0.0), but the latest version is 2.3.1 and many python packages have a lower-bound of 2.0.0 and above.

Describe the solution you'd like

Remove google-cloud-core fr

Use case

Polyaxon tracking can be used to automatically log all information generated by Ludwig.

We should probably think about adding support for Polyaxon's tracking module in Ludwig contrib.

Contact Details [Optional]

support@zenml.io

Describe the feature you'd like

When someone uses the zenml secret register --help command, the formatting of the CLI help information comes out wrong with line breaks not really happening. It isn't possible to read the text printed to the terminal as executed within [the register_secret function](https://github.com/zenml-io/zenml/blob/373

https://docs.deepchecks.com/stable/user-guide/vision/data-classes/index.html#what-do-you-need-to-implement
The faulty links are marked in yellow

Feature request

In several places we use multiple dispatch. Right now the types to dispatch on are configured separately. Could we infer the types to dispatch on from Python type hints? That would simplify the code.

Motivation

Instead of:

@dispatch.expectation.register(Gaussian, kernels.Sum, InducingPoints, NoneType, NoneType)
def expectation_gaussian_sum_inducingpoints(
    

Have a tutorial for dealing with categorical features in a machine learning problem, including the usage of tools inside fklearn.training.transformation.

In augmentation, elastic_transform, it only applies a random transform on one input image array. I would think to be used for training, the image and mask pair should be transform in the same way. However, this single-input-image, single-output-image method makes it very inconvenient. Could we deform a list of images (np.arrays) using the same transformation in this method ? Thanks!

• correcting handling asserts
  • replacing assert condition with the pattern
    if not condition: raise AssertionError()

If it doesn't already exist in the NannyML package (I didn't find it), it would be nice to have a collection of bare-bones functions to predict performance using only a list / array / series of y_pred_proba values.