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pollfly
2023-11-05 10:30:37 +02:00
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2
docs/guides/frameworks/scikit-learn/sklearn_joblib_example.md
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@@ -1,5 +1,5 @@
---
title: Scikit-Learn with Joblib
title: scikit-learn with Joblib
---
The [sklearn_joblib_example.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/scikit-learn/sklearn_joblib_example.py)

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docs/guides/pipeline/pipeline_controller.md
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@@ -50,7 +50,7 @@ The sections below describe in more detail what happens in the controller task a
1. Build the pipeline (see [PipelineController.add_step](../../references/sdk/automation_controller_pipelinecontroller.md#add_step)
method for complete reference):
The pipeline's [first step](#step-1---downloading-the-datae) uses the pre-existing task
The pipeline's [first step](#step-1---downloading-the-data) uses the pre-existing task
`pipeline step 1 dataset artifact` in the `examples` project. The step uploads local data and stores it as an artifact.
```python

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docs/guides/reporting/3d_plots_reporting.md
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@@ -27,7 +27,7 @@ Logger.current_logger().report_surface(
zaxis="title Z",
)
```
Visualize the reported surface plot in **PLOTS**.
View the reported surface plot in **PLOTS**.
![Surface plot](../../img/examples_reporting_02.png)
@@ -49,5 +49,5 @@ Logger.current_logger().report_scatter3d(
)
```
Visualize the reported 3D scatter plot in **PLOTS**.
View the reported 3D scatter plot in **PLOTS**.
![3d scatter plot](../../img/examples_reporting_01.png)

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docs/guides/reporting/clearml_logging_example.md
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@@ -17,8 +17,8 @@ In the ``clearml`` GitHub repository, this example includes a clickable icon to
## Scalars
To reports scalars, call the [Logger.report_scalar](../../references/sdk/logger.md#report_scalar)
method. The scalar plots appear in the **web UI** in **SCALARS**.
To reports scalars, call [Logger.report_scalar()](../../references/sdk/logger.md#report_scalar).
The scalar plots appear in the **web UI** in **SCALARS**.
```python
# report two scalar series on two different graphs
@@ -44,7 +44,7 @@ Plots appear in **PLOTS**.
### 2D Plots
Report 2D scatter plots by calling the [Logger.report_scatter2d](../../references/sdk/logger.md#report_scatter2d) method.
Report 2D scatter plots by calling [Logger.report_scatter2d()](../../references/sdk/logger.md#report_scatter2d).
Use the `mode` parameter to plot data points as markers, or both lines and markers.
```python
@@ -67,7 +67,7 @@ logger.report_scatter2d(
### 3D Plots
To plot a series as a 3D scatter plot, use the [Logger.report_scatter3d](../../references/sdk/logger.md#report_scatter3d) method.
To plot a series as a 3D scatter plot, use [Logger.report_scatter3d()](../../references/sdk/logger.md#report_scatter3d).
```python
# report 3d scatter plot
@@ -85,8 +85,7 @@ logger.report_scatter3d(
![3d scatter plot](../../img/colab_explicit_reporting_05.png)
To plot a series as a surface plot, use the [Logger.report_surface](../../references/sdk/logger.md#report_surface)
method.
To plot a series as a surface plot, use [Logger.report_surface()](../../references/sdk/logger.md#report_surface).
```python
# report 3d surface

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docs/guides/reporting/model_config.md
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@@ -25,8 +25,7 @@ output_model = OutputModel(task=task)
## Label Enumeration
Set the model's label enumeration using the [`OutputModel.update_labels`](../../references/sdk/model_outputmodel.md#update_labels)
method.
Set the model's label enumeration using [`OutputModel.update_labels()`](../../references/sdk/model_outputmodel.md#update_labels).
```python
labels = {"background": 0, "cat": 1, "dog": 2}
@@ -34,8 +33,8 @@ output_model.update_labels(labels)
```
## Registering Models
Register a previously trained model using the [`OutputModel.update_weights`](../../references/sdk/model_outputmodel.md#update_weights)
method. The example code uses a model stored in S3.
Register a previously trained model using [`OutputModel.update_weights()`](../../references/sdk/model_outputmodel.md#update_weights).
The example code uses a model stored in S3.
```python
# Manually log a model file, which will have the labels connected above

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docs/guides/ui/building_leader_board.md
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@@ -51,7 +51,7 @@ The experiments table allows filtering experiments by experiment name, type, and
* **Aborted** - The experiment ran and was manually or programmatically terminated.
* **Published** - The experiment is not running, it is preserved as read-only.
## Step 3: Hide the Defaults Column
## Step 3: Hide the Default Columns
Customize the columns on the tracking leaderboard by hiding any of the default columns shown below.