Release/1.11.0 (#815)

CHANGELOG.md

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 ## Unreleased
 ### Added
-- LSTM based RNN and native deep models base classes ([#776](https://github.com/tinkoff-ai/etna/pull/776))
-- Lambda transform ([#762](https://github.com/tinkoff-ai/etna/issues/762))
-- assemble pipelines ([#774](https://github.com/tinkoff-ai/etna/pull/774))
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-- Tests on in-sample, out-sample predictions with gap for all models ([#785](https://github.com/tinkoff-ai/etna/pull/786))
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+## [1.11.0] - 2022-07-25
+### Added
+- LSTM based RNN and native deep models base classes ([#776](https://github.com/tinkoff-ai/etna/pull/776))
+- Lambda transform ([#762](https://github.com/tinkoff-ai/etna/issues/762))
+- assemble pipelines ([#774](https://github.com/tinkoff-ai/etna/pull/774))
+- Tests on in-sample, out-sample predictions with gap for all models ([#785](https://github.com/tinkoff-ai/etna/pull/786))
 ### Changed
 - Add columns and mode parameters in plot_correlation_matrix ([#726](https://github.com/tinkoff-ai/etna/pull/753))
 - Add CatBoostPerSegmentModel and CatBoostMultiSegmentModel classes, deprecate CatBoostModelPerSegment and CatBoostModelMultiSegment ([#779](https://github.com/tinkoff-ai/etna/pull/779))
-- 
 - Allow Prophet update to 1.1 ([#799](https://github.com/tinkoff-ai/etna/pull/799))
-- 
 - Make LagTransform, LogTransform, AddConstTransform vectorized ([#756](https://github.com/tinkoff-ai/etna/pull/756))
 - Improve the behavior of plot_feature_relevance visualizing p-values ([#795](https://github.com/tinkoff-ai/etna/pull/795))
 - Update poetry.core version ([#780](https://github.com/tinkoff-ai/etna/pull/780))
-- 
 - Make native prediction intervals for DeepAR ([#761](https://github.com/tinkoff-ai/etna/pull/761))
 - Make native prediction intervals for TFTModel ([#770](https://github.com/tinkoff-ai/etna/pull/770))
 - Test cases for testing inference of models ([#794](https://github.com/tinkoff-ai/etna/pull/794))
 - Wandb.log to WandbLogger ([#816](https://github.com/tinkoff-ai/etna/pull/816))
 ### Fixed
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 - Fix missing prophet in docker images ([#767](https://github.com/tinkoff-ai/etna/pull/767))
 - Add `known_future` parameter to CLI ([#758](https://github.com/tinkoff-ai/etna/pull/758))
 - FutureWarning: The frame.append method is deprecated. Use pandas.concat instead ([#764](https://github.com/tinkoff-ai/etna/pull/764))
 - Correct ordering if multi-index in backtest ([#771](https://github.com/tinkoff-ai/etna/pull/771))
 - Raise errors in models.nn if they can't make in-sample and some cases out-sample predictions ([#813](https://github.com/tinkoff-ai/etna/pull/813))
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 - Teach BATS/TBATS to work with in-sample, out-sample predictions correctly ([#806](https://github.com/tinkoff-ai/etna/pull/806))
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 - Github actions cache issue with poetry update ([#778](https://github.com/tinkoff-ai/etna/pull/778))
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 ## [1.10.0] - 2022-06-12
 ### Added

README.md

@@ -218,14 +218,19 @@ To ask the questions or discuss the library you can join our [telegram chat](t.m
 [Artem Makhin](https://github.com/Ama16),
 [Ivan Mitskovets](https://github.com/imitskovets),
 [Albina Munirova](https://github.com/albinamunirova),
-[Nikolay Romantsov](https://github.com/WinstonDovlatov),
-[Julia Shenshina](https://github.com/julia-shenshina)
+[Julia Shenshina](https://github.com/julia-shenshina),
+[Yuriy Tarasyuk](https://github.com/DBcreator),
+[Konstantin Vedernikov](https://github.com/scanhex12)
 
 ### ETNA.Contributors
 
 [Artem Levashov](https://github.com/soft1q),
 [Aleksey Podkidyshev](https://github.com/alekseyen),
-[Carlosbogo](https://github.com/Carlosbogo)
+[Carlosbogo](https://github.com/Carlosbogo),
+[Nikolay Romantsov](https://github.com/WinstonDovlatov),
+[mvakhmenin](https://github.com/mvakhmenin),
+[Pacman1984](https://github.com/Pacman1984),
+[looopka](https://github.com/looopka)
 
 ## License
 

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "etna"
-version = "1.10.0"
+version = "1.11.0"
 repository = "https://github.com/tinkoff-ai/etna"
 readme = "README.md"
 description = "ETNA is the first python open source framework of Tinkoff.ru AI Center. It is designed to make working with time series simple, productive, and fun."