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?

I naively tried to do dd.merge(a, b, on="column_with_ten_values"), where a and b were both large DataFrames with thousands of partitions each.

Eventually the compute failed with:

[File /opt/conda/envs/coiled/lib/python3.9/site-packages/dask/dataframe/multi.py:275, in merge_chunk()

File /opt/conda/envs/coiled/lib/python3.9/site-packages/pandas/core/frame.py:9329, i

We currently fit and predict upon loading autosklearn.experimental.askl2 for the first time. In environments with a non-persistent filesystem (autosklearn is installed into a new filesystem each time), this can add quite a bit of time delay as experienced in #1362

It seems more applicable to export the

• As a user, I wish featuretools dfs would take a string as cutoff_time aswell as a datetime object

Code Example

fm, features = ft.dfs(entityset=es,
                      target_dataframe_name='customers',
                      cutoff_time="2014-1-1 05:00",
                      instance_ids=[1],
                      cutoff_time_in_index=True)

as well as

The first entry is being eaten by the Differencer in its current standard setting, which may cause user frustration, especially when combined with a pipeline (which is its "typical use"), see e.g., here: alan-turing-institute/sktime#2452

We should add an NA handling parameter setting and make the default to fill in sth for the first value, e.g., a difference from an

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: [email protected]

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