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replaced dvc run with stage and exp run
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iesahin committed Jan 26, 2022
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12 changes: 6 additions & 6 deletions content/docs/command-reference/dag.md
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### Directed acyclic graph

A data pipeline, in general, is a series of data processing
[stages](/doc/command-reference/run) (for example, console commands that take an
input and produce an outcome). The connections between stages are formed by the
<abbr>output</abbr> of one turning into the <abbr>dependency</abbr> of another.
A pipeline may produce intermediate data, and has a final result.
[stages](/doc/command-reference/stage) (for example, console commands that take
an input and produce an outcome). The connections between stages are formed by
the <abbr>output</abbr> of one turning into the <abbr>dependency</abbr> of
another. A pipeline may produce intermediate data, and has a final result.

Data science and machine learning pipelines typically start with large raw
datasets, include intermediate featurization and training stages, and produce a
final model, as well as accuracy [metrics](/doc/command-reference/metrics).

In DVC, pipeline stages and commands, their data I/O, interdependencies, and
results (intermediate or final) are specified in `dvc.yaml`, which can be
written manually or built using the helper command `dvc run`. This allows DVC to
restore one or more pipelines later (see `dvc repro`).
written manually or built using the helper command `dvc stage add`. This allows
DVC to restore one or more pipelines later (see `dvc exp run` and `dvc repro`).

> DVC builds a dependency graph
> ([DAG](https://en.wikipedia.org/wiki/Directed_acyclic_graph)) to do this.

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