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GluonTS documentation

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GluonTS documentation

Getting started

Installation
Background
Concepts
Available models

Tutorials

Basic Usage
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Data Manipulation
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- Splitting datasets into training and test
- Synthetic data generation
Advanced
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- Custom models with PyTorch
- Tuning models with Optuna

API docs

API Docs
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- gluonts.core package
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  - gluonts.core.serde package
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  - gluonts.core.component module
  - gluonts.core.settings module
- gluonts.dataset package
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  - gluonts.dataset.arrow package
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  - gluonts.dataset.artificial package
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    - gluonts.dataset.artificial.ar_p module
    - gluonts.dataset.artificial.recipe module
  - gluonts.dataset.repository package
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    - gluonts.dataset.repository.datasets module
  - gluonts.dataset.schema package
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    - gluonts.dataset.schema.translate module
  - gluonts.dataset.common module
  - gluonts.dataset.field_names module
  - gluonts.dataset.hierarchical module
  - gluonts.dataset.jsonl module
  - gluonts.dataset.loader module
  - gluonts.dataset.multivariate_grouper module
  - gluonts.dataset.pandas module
  - gluonts.dataset.split module
  - gluonts.dataset.stat module
  - gluonts.dataset.util module
- gluonts.ev package
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- gluonts.evaluation package
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  - gluonts.evaluation.backtest module
  - gluonts.evaluation.metrics module
- gluonts.ext package
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  - gluonts.ext.naive_2 package
  - gluonts.ext.prophet package
  - gluonts.ext.r_forecast package
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    - gluonts.ext.r_forecast.util module
  - gluonts.ext.rotbaum package
  - gluonts.ext.hierarchicalforecast module
  - gluonts.ext.statsforecast module
- gluonts.meta package
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- gluonts.model package
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- gluonts.mx package
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- gluonts.shell package
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  - gluonts.shell.sagemaker package
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  - gluonts.shell.serve package
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    - gluonts.shell.serve.app module
  - gluonts.shell.env module
  - gluonts.shell.exceptions module
  - gluonts.shell.train module
  - gluonts.shell.util module
- gluonts.testutil package
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- gluonts.time_feature package
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- gluonts.torch package
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  - gluonts.torch.distributions package
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  - gluonts.torch.model package
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    - gluonts.torch.model.d_linear package
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    - gluonts.torch.model.deep_npts package
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      - gluonts.torch.model.deep_npts.scaling module
    - gluonts.torch.model.deepar package
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    - gluonts.torch.model.i_transformer package
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    - gluonts.torch.model.lag_tst package
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    - gluonts.torch.model.mqf2 package
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    - gluonts.torch.model.patch_tst package
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    - gluonts.torch.model.simple_feedforward package
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    - gluonts.torch.model.tft package
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    - gluonts.torch.model.tide package
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    - gluonts.torch.model.wavenet package
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    - gluonts.torch.model.estimator module
    - gluonts.torch.model.forecast module
    - gluonts.torch.model.forecast_generator module
    - gluonts.torch.model.lightning_util module
    - gluonts.torch.model.predictor module
  - gluonts.torch.modules package
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  - gluonts.torch.batchify module
  - gluonts.torch.component module
  - gluonts.torch.prelude module
  - gluonts.torch.scaler module
  - gluonts.torch.util module
- gluonts.transform package
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- gluonts.zebras package
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  - gluonts.zebras.schema module
- gluonts.env module
- gluonts.exceptions module
- gluonts.gluonts_tqdm module
- gluonts.itertools module
- gluonts.json module
- gluonts.maybe module
- gluonts.util module

Developing

Contributing Guidelines
Development Setup

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gluonts.mx.distribution.dirichlet_multinomial module#

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