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updated links to data-access and data-versioning in blog
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iesahin committed Feb 20, 2021
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2 changes: 1 addition & 1 deletion content/blog/2020-10-12-october-20-dvc-heartbeat.md
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Expand Up @@ -107,7 +107,7 @@ few weeks, so stay tuned. Another big initative is adding videos to our docs:
since video seems like a popular format for a lot of learners, we're working to
supplement our official docs with embedded videos. Check out our first
installment on the
[Getting Started with Data Versioning](https://dvc.org/doc/start/data-versioning).
[Getting Started with Data Versioning](https://dvc.org/doc/start/data-and-model-versioning).

https://youtu.be/kLKBcPonMYw

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2 changes: 1 addition & 1 deletion content/blog/2020-11-11-november-20-dvc-heartbeat.md
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Expand Up @@ -64,7 +64,7 @@ welcome referrals if you know a good candidate)!

We're continuing to develop our video docs, and now half of our "Getting
Started" section has video accompaniments. Check out our latest release on
[data access with DVC](https://dvc.org/doc/start/data-access):
[data access with DVC](https://dvc.org/doc/start/data-and-model-access):

https://youtu.be/EE7Gk84OZY8

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8 changes: 4 additions & 4 deletions content/blog/2020-12-18-december-20-dvc-heartbeat.md
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Expand Up @@ -53,11 +53,11 @@ As you may have heard
on adding complete video docs to the "Getting Started" section of the DVC site.
We now have 100% coverage! We have videos that mirror the tutorials for:

- [Data versioning](https://dvc.org/doc/start/data-versioning) - how to use Git
and DVC together to track different versions of a dataset
- [Data versioning](https://dvc.org/doc/start/data-and-model-versioning) - how
to use Git and DVC together to track different versions of a dataset

- [Data access](https://dvc.org/doc/start/data-access) - how to share models and
datasets across projects and environments
- [Data access](https://dvc.org/doc/start/data-and-model-access) - how to share
models and datasets across projects and environments

- [Pipelines](https://dvc.org/doc/start/data-pipelines) - how to create
reproducible pipelines to transform datasets to features to models
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