Stone_Red/dvc
1
0
Fork 0
mirror of https://github.com/Stone-Red-Code/dvc.git synced 2026-11-01 23:08:43 +01:00
Code Issues Packages Projects Releases Wiki Activity

readme: improve and reformat How it works

Browse Source
This commit is contained in:
Jorge Orpinel Perez
2022-07-20 07:16:26 +05:45
committed by skshetry
parent 94eec50d27
commit ec4d61e2b1
1 changed files with 10 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.rst
+10 -12
View File
@@ -38,23 +38,21 @@ How DVC works
We encourage you to read our `Get Started <https://dvc.org/doc/get-started>`_ guide to better understand what DVC
is and how it can fit your scenarios.
The easiest (but not perfect!) *analogy* to describe it: DVC is Git (or Git-LFS to be precise) & Makefiles
made right and tailored specifically for ML and Data Science scenarios.
The easiest (but not perfect!) *analogy* to describe it: DVC is Git for data & Makefiles tailored specifically for ML and Data Science scenarios.
#. ``Git/Git-LFS`` part - DVC helps store and share data artifacts and models, connecting them with a Git repository.
#. ``Makefile``\ s part - DVC describes how one data or model artifact was built from other data and code.
#. **Git** part - DVC helps store and share data artifacts (like Git-LFS but without a server) and models, connecting them with a Git repository.
#. **Make** part - DVC describes how data or model artifacts are built from other data and code -- a data pipeline.
DVC usually runs along with Git. Git is used as usual to store and version code (including DVC meta-files). DVC helps
to store data and model files seamlessly out of Git, while preserving almost the same user experience as if they
were stored in Git itself. To store and share the data cache, DVC supports multiple remotes - any cloud (S3, Azure,
Google Cloud, etc) or any on-premise network storage (via SSH, for example).
DVC usually works on top of Git.
Git is used as usual to store and version code (including DVC meta-files).
DVC helps to store data and model files seamlessly out of Git, while preserving almost the same user experience as if they were stored in Git itself.
To store and share the *data cache*, DVC supports multiple remotes - any cloud (S3, Azure, Google Cloud, etc.) or on-premise network storage (via SSH, for example).
|Flowchart|
The DVC pipelines (computational graph) feature connects code and data together. It is possible to explicitly
specify all steps required to produce a model: input dependencies including data, commands to run,
and output information to be saved. See the quick start sections below or
the `Get Started <https://dvc.org/doc/get-started>`_ tutorial to learn more.
DVC pipelines (computational graphs) connect code and data together.
They specify all steps required to produce a model: input dependencies including code, data, commands to run; and output information to be saved.
Quick start
===========