New Operator

Describe the operator

Why is this operator necessary? What does it accomplish?

This is a frequently used operator in tensorflow/keras

Can this operator be constructed using existing onnx operators?

If so, why not add it as a function?

I don't know.

Is this operator used by any model currently? Which one?

Are you willing to contribute it?

Array.reshape "only allows for reshapings that collapse or merge dimensions" (xref dask/dask#2561). However, when you try to do one of these unsupported reshapings, the error message Shapes not compatible does not make it at all clear that what you're asking for just isn't supported by dask. Instead, it sounds as though your inputs are invalid.

A more descriptive e

It seems there is no validation on fit_ensemble when ensemble size is 0, causing an issue to appear as seen in #1327

• transform_primitive.py is becoming very large. I suggest splitting out into separate files.
• We could split this file up by groups (such as LatLong transform primitives in 1 file).

As the title says, there should be a short section on predicting residuals predict_residuals to the forecasting tutorial - both about getting all the in-sample residuals (default arguments) and getting specific residuals out-of-sample or in-sample.

Yes

readthedocs analytics says that we have several search results that yield little or no useful results. Let's improvethose:

• gpu (only 2 results): make sure that explanation of device parameter mentions gpu as well
• gridsearch (0 results): make sure to include the term gridsearch in the meta data of

Related: awslabs/autogluon#1479

Add a scikit-learn compatible API wrapper of TabularPredictor:

• TabularClassifier
• TabularRegressor

Required functionality (may need more than listed):

• init API
• fit API
• predict API
• works in sklearn pipelines

Hello everyone,

First of all, I want to take a moment to thank all contributors and people who supported this project in any way ;) you are awesome!

If you like the project and have any interest in contributing/maintaining it, you can contact me here or send me a msg privately:

• Email: nidhalbacc@gmail.com

PS: You need to be familiar with python and machine learning