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2023-11-23 15:04:17 +02:00
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docs/getting_started/mlops/mlops_best_practices.md
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@@ -31,7 +31,7 @@ Once you have a Task in ClearML, you can clone and edit its definitions in the U
## Manage Your Data
Use [ClearML Data](../../clearml_data/clearml_data.md) to version your data, then link it to running experiments for easy reproduction.
Make datasets machine agnostic (i.e. store original dataset in a shared storage location, e.g. shared-folder / S3 / Gs / Azure).
ClearML Data supports efficient Dataset storage and caching, differentiable & compressed.
ClearML Data supports efficient Dataset storage and caching, differentiable and compressed.
## Scale Your Work
Use [ClearML Agent](../../clearml_agent.md) to scale work. Install the agent machines (remote or local) and manage

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docs/getting_started/mlops/mlops_first_steps.md
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@@ -21,7 +21,7 @@ ClearML Agent was designed to deal with such issues and more! It is a tool respo
machine of choice through the ClearML WebApp with no need for additional code.
The agent will set up the environment for a specific Task’s execution (inside a Docker, or bare-metal), install the
required python packages, and execute & monitor the process.
required python packages, and execute and monitor the process.
## Set up an Agent