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docs/clearml_serving/clearml_serving.md
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@ -22,7 +22,7 @@ solution.
* Multi models per serving service * Multi models per serving service
* Multi-service support (fully separated multiple serving service running independently) * Multi-service support (fully separated multiple serving service running independently)
* Multi cluster support * Multi cluster support
* Out-of-the-box node auto-scaling based on load/usage * Out-of-the-box node autoscaling based on load/usage
* Efficient * Efficient
* Multi-container resource utilization * Multi-container resource utilization
* Support for CPU & GPU nodes * Support for CPU & GPU nodes

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docs/fundamentals/task.md
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@ -112,7 +112,7 @@ Available task types are:
* *optimizer* - A specific type of controller for optimization tasks (e.g. [hyperparameter optimization](hpo.md)) * *optimizer* - A specific type of controller for optimization tasks (e.g. [hyperparameter optimization](hpo.md))
* *service* - Long lasting or recurring service (e.g. server cleanup, auto ingress, sync services etc.) * *service* - Long lasting or recurring service (e.g. server cleanup, auto ingress, sync services etc.)
* *monitor* - A specific type of service for monitoring * *monitor* - A specific type of service for monitoring
* *application* - A task implementing custom applicative logic, like [auto-scaler](../guides/services/aws_autoscaler.md) * *application* - A task implementing custom applicative logic, like [autoscaler](../guides/services/aws_autoscaler.md)
or [clearml-session](../apps/clearml_session.md) or [clearml-session](../apps/clearml_session.md)
* *data_processing* - Any data ingress / preprocessing (see [ClearML Data](../clearml_data/clearml_data.md)) * *data_processing* - Any data ingress / preprocessing (see [ClearML Data](../clearml_data/clearml_data.md))
* *qc* - Quality Control (e.g. evaluating model performance vs. blind dataset) * *qc* - Quality Control (e.g. evaluating model performance vs. blind dataset)

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docs/guides/clearml_agent/executable_exp_containers.md
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title: Executable Experiment Containers title: Executable Experiment Containers
--- ---
This tutorial demonstrates using [`clearml-agent`](../../clearml_agent.md)’s [`build`](../../clearml_agent/clearml_agent__ref#build) This tutorial demonstrates using [`clearml-agent`](../../clearml_agent.md)’s [`build`](../../clearml_agent/clearml_agent_ref.md#build)
command to package an experiment into an executable container. In this example, you will build a Docker image that, when command to package an experiment into an executable container. In this example, you will build a Docker image that, when
run, will automatically execute the [keras_tensorboard.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/keras_tensorboard.py) run, will automatically execute the [keras_tensorboard.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/keras_tensorboard.py)
script. script.

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docs/guides/ide/google_colab.md
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@ -8,7 +8,7 @@ compute provided by google.
Users can transform a Google Colab instance into an available resource in ClearML using [ClearML Agent](../../clearml_agent.md). Users can transform a Google Colab instance into an available resource in ClearML using [ClearML Agent](../../clearml_agent.md).
This tutorial goes over how to create a ClearML worker node in a Google Colab notebook. Once the worker is up This tutorial goes over how to create a ClearML worker node in a Google Colab notebook. Once the worker is up
and running, users can send Tasks to be executed on the Google Colab's HW. and running, users can send Tasks to be executed on Google Colab's HW.
## Prerequisites ## Prerequisites
* Be signed up for ClearML (Or have a server deployed). * Be signed up for ClearML (Or have a server deployed).

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docs/webapp/webapp_overview.md
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@ -52,7 +52,7 @@ email > click **ADD** > page redirects to the [Users & Groups](webapp_profile.md
* **Logout** of ClearML * **Logout** of ClearML
### Finding What You're Looking for ### Finding What You're Looking for
Use the search bar <img src="/docs/latest/icons/ico-search.svg" alt="Magnifying glass" className="icon size-sm space-sm" /> Use the search bar <img src="/docs/latest/icons/ico-search.svg" alt="Magnifying glass" className="icon size-md space-sm" />
to find your ClearML resources. to find your ClearML resources.
To search using regex, click the `.*` icon on the search bar. To search using regex, click the `.*` icon on the search bar.
@ -80,10 +80,10 @@ and [datasets](datasets/webapp_dataset_page.md)) provide column filters to easil
::: :::
### Helpful Resources ### Helpful Resources
Click the help menu button <img src="/docs/latest/icons/ico-help-outlined.svg" alt="Help menu" className="icon size-sm space-sm" /> Click the help menu button <img src="/docs/latest/icons/ico-help-outlined.svg" alt="Help menu" className="icon size-md space-sm" />
in the top right corner of the web UI screen to access the self-help resources including: in the top right corner of the web UI screen to access the self-help resources including:
* ClearML Python Package setup - Instruction to get started with the `clearml` Python package * ClearML Python Package setup - Instruction to get started with the `clearml` Python package
* [ClearML on YouTube](https://www.youtube.com/c/ClearML/featured) <img src="/docs/latest/icons/ico-youtube.svg" alt="Youtube" className="icon size-sm space-sm" /> - Instructional videos on integrating ClearML into your workflow * [ClearML on YouTube](https://www.youtube.com/c/ClearML/featured) <img src="/docs/latest/icons/ico-youtube.svg" alt="Youtube" className="icon size-md space-sm" /> - Instructional videos on integrating ClearML into your workflow
* Online Documentation * Online Documentation
* Pro Tips - Tips for working with ClearML efficiently * Pro Tips - Tips for working with ClearML efficiently
* [Contact Us](https://clear.ml/contact-us) - Quick access to ClearML contact form * [Contact Us](https://clear.ml/contact-us) - Quick access to ClearML contact form