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Description
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AutoML Sweepable API (Proposal: Sweepable API #5993)
- implementation (Use SweepablePipeline #6285)
- make it public (make AutoMLExperiment public && some small refactor #6173)
- documents
- code example
- jupyter notebook example
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AutoML Featurizer API (add auto featurizer api #6187)
- implementation (implement auto featurizer #6205) (add image featurizer to AutoFeaturizer #6261)
- make it public
- documents
- code example
- image classification with image featurizer
- jupyter notebook example
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AutoML Experiment API (Proposal: Experiment API #6118 )
- implementation
- make it pubic (make AutoMLExperiment public && some small refactor #6173)
- documents [Create example for AutoMLExperiment in api doc. #6589]
- code example
- jupyter notebook example
- titanic
- taxi-fare
- iris
- luna forecasting using regression
- needs more
- reimplement existing experiment using AutoML Experiment API
- BinaryExperiment (reimplement binary experiment using AutoMLExperiment #6246)
- Multiclass Experiment (improve multiclassification using AutoMLExperiment #6270)
- Regression (Improve RegressionExpeirment using AutoMLExperiment #6338)
- Recommendation
- Ranking
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AutoML Advance Feature
- continue training [Add ITrialResultManager for continue training in AutoML #6335]
- exit strategy [Add MaxModelToExplore exit strategy to AutoMLExperiment. #6402 ]
- limit resource (CPU/memory) [Add SetMaximumMemoryUsageInMegaByte in AutoMLExperiment #6305]