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ml

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.

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askhade
askhade commented Jan 19, 2021

Add a new API for converting a model to external data. Today the conversion happens in 2 steps
external_data_helper.convert_model_to_external_data(<model>, <all_tensors_to_one_file>, <size_threshold>) save_model(model, output_path)
We want to add another api which combines the 2 steps
`
save_model_to_external_data(, <output_

ameyaparab28
ameyaparab28 commented Mar 1, 2021

Willingness to contribute

The MLflow Community encourages new feature contributions. Would you or another member of your organization be willing to contribute an implementation of this feature (either as an MLflow Plugin or an enhancement to the MLflow code base)?

  • Yes. I can contribute this feature independently.
  • Yes. I would be willing to contribute this feature with guidance
justinormont
justinormont commented Jan 25, 2021

Remove logging line, or modify from ch.Info to ch.Trace:
http://www.shanzhaw.com/dotnet/machinelearning/blob/5dbfd8acac0bf798957eea122f1413209cdf07dc/src/Microsoft.ML.Mkl.Components/SymSgdClassificationTrainer.cs#L813

For my text dataset, this logging line dumps ~100 pages of floats to my console. That level of verbosity is unneeded at the Info level.

I'd recommend just removing the loggin

Open

[BUG]

2
mynameisvinn
mynameisvinn commented Mar 9, 2021

???? Bug Report

?? Current Behavior

Hub's version info is present in two locations, setup.py and hub/version.py. As result, the released version displays the wrong version info (1.2.3 instead of 1.3.0) when users do hub --version.

?? Possible Solution (optional)

Remove version info from setup.py.

mmlspark
brunocous
brunocous commented Sep 2, 2020

I have a simple regression task (using a LightGBMRegressor) where I want to penalize negative predictions more than positive ones. Is there a way to achieve this with the default regression LightGBM objectives (see https://lightgbm.readthedocs.io/en/latest/Parameters.html)? If not, is it somehow possible to define (many example for default LightGBM model) and pass a custom regression objective?

sisidra
sisidra commented Dec 30, 2020

Currently com.spotify.scio.bigtable.syntax.ScioContextOps#updateNumberOfBigtableNodes updates all clusters for the instance.
That is not desired behaviour if each cluster is dedicated for specific task - one for batch jobs, another for service, etc.
Desired API is to allow change node count for only specific cluster (dedicated for batch jobs).

Proposed API change:

- def updateNumberOf
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