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1. Commits on Jan 6, 2022

   • Update broken image link

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2. Commits on Jun 3, 2021

   • LICENSE: Update to MIT

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   • Bump version to v1.1.1

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   • Add rmse calculation and integrate with model metrics

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   • feat (forecasting): [WIP] Add support for ARIMA model

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   • feat (forecasting): Add support for custom train test split in setup function

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   • feat (entity): Add size to timeseries class

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3. Commits on May 30, 2021

   • validation: Add rmse metric

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4. Commits on May 28, 2021

   • examples: Update forecasting and anomaly_detection

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   • eda: Add KPSS stationarity test to `test_stationarity` method

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   • models/forecasting: Add ARIMA model

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   • data_loader: Improve auto date format detection

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5. Commits on May 9, 2021

   • logo: Update logo

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6. Commits on May 8, 2021

   • readme: Fix minor typo

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   • readme: Update headline and enhance getting started

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   • readme: Add getting started guide

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   • setup: Bump version to v1.1.0

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   • readme: Enhance readme and add pytsal logo

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   • examples: Add tutorials (ipynb notebooks) for forecasting and anomaly detection

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   • anomaly: Enhance interface and add setup helper

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   • examples: Minor enhancements to examples

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   • dataset: Use remote datasets from github over local files

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   • validation: Set figure size for validation plot

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   • Add pytsal logo

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7. Commits on Apr 22, 2021

   • Bump patch version (v1.0.2)

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   • Update brutlag algorithm params

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   • requirements: Remove scikit-learn

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   • Add model comparison plot and better scoring methods

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8. Commits on Apr 21, 2021

   • Add sckit-learn as dependency

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   • Add github action to publish to pypi on release

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   • Update examples

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   • Bump version to v1.0.0

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   • Add github action to publish to pypi

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   • Add github issue templates

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   • Implement concrete class and helpers for holt winter forecasting

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