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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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dbczumar
dbczumar commented Sep 18, 2021

MLflow Roadmap Item

This is an MLflow Roadmap item that has been prioritized by the MLflow maintainers. We're seeking help with the implementation of roadmap items tagged with the help wanted label.

For requirements clarifications and implementation questions, or to request a PR review, please tag @BenWilson2 in your communications related to this issue.

Proposal Summary

Includ

justinormont
justinormont commented Jan 25, 2021

Remove logging line, or modify from ch.Info to ch.Trace:
https://github.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

metaflow
tuulos
tuulos commented Sep 7, 2021

With a config like this

{
    "METAFLOW_DATASTORE_SYSROOT_S3": "s3://mf-test/metaflow/",
}

(note a slash after METAFLOW_DATASTORE_SYSROOT_S3)

metaflow.S3(run=self).put* produces double-slashes like here:

s3://mf-test/metaflow//data/DataLoader/1630978962283843/month=01/data.parquet

The trailing slash in the config shouldn't make a difference

ZoranPandovski
ZoranPandovski commented Oct 13, 2021

When users create a connection to the database it will be useful to show them tips with a list of tables. To be able to do this we need a new method get_tables_list implemented in the PostgreSQL integration class.

Steps 🕵️‍♂️ 🕵️‍♀️

SynapseML
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?

achals
achals commented Jul 7, 2021

Expected Behavior

When an entity is removed from the feature repo, it should be removed from the feature registry.

Current Behavior

Entities are only added, never removed from the Registry. This is a storage leak of sorts.

Steps to reproduce

  • feast init
  • In the new feature repo, feast apply
  • Add a new entity in the feature repo. feast apply.
  • Remove the new en
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