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Notice of new org change in the readme #1970

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Aug 29, 2023
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Notice of new org change in the readme #1970

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miguelgfierro Aug 18, 2023
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miguelgfierro Aug 18, 2023
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miguelgfierro Aug 18, 2023
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6 changes: 5 additions & 1 deletion NEWS.md
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# What's New

## Update August 18, 2023

We moved to a new organization! Now to access the repo, instead of going to https://github.com/microsoft/recommenders, you need to go to https://github.com/recommenders-team/recommenders. The old URL will still resolve to the new one, but we recommend you to update your bookmarks.

## Update February 7, 2023

We reached 15,000 stars!!

## Update July, 2022
## Update July 20, 2022

We have a new release [Recommenders 1.1.1](https://github.com/microsoft/recommenders/releases/tag/1.1.1)!

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10 changes: 2 additions & 8 deletions README.md
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[![Documentation Status](https://readthedocs.org/projects/microsoft-recommenders/badge/?version=latest)](https://microsoft-recommenders.readthedocs.io/en/latest/?badge=latest)

## What's New (April, 2023)
## What's New (August, 2023)

We reached 15,000 stars!!

Our latest release is [Recommenders 1.1.1](https://github.com/microsoft/recommenders/releases/tag/1.1.1)!

We have introduced a new way of testing our repository using [AzureML](https://azure.microsoft.com/en-us/services/machine-learning/). With AzureML we are able to distribute our tests to different machines and run them in parallel. This allows us to test our repository on a wider range of machines and provides us with a much faster test cycle. Our total computation time went from around 9h to 35min, and we were able to reduce the costs by half. See more details [here](tests/README.md).

We also made other improvements like faster evaluation metrics and improving SAR algorithm.
We moved to a new organization! Now to access the repo, instead of going to https://github.com/microsoft/recommenders, you need to go to https://github.com/recommenders-team/recommenders. The old URL will still resolve to the new one, but we recommend you to update your bookmarks.

Starting with release 0.6.0, Recommenders has been available on PyPI and can be installed using pip!

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