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Change terminology (#1028)
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@@ -12,7 +12,7 @@ The example does the following:
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1. Specifies accuracy as the metric, and uses two callbacks: a TensorBoard callback and a model checkpoint callback.
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1. During script execution, creates an experiment named `notebook example` in the `examples` project.
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1. During script execution, creates a task named `notebook example` in the `examples` project.
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## Scalars
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@@ -69,10 +69,10 @@ Text printed to the console for training appears in **CONSOLE**.
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## Artifacts
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Models created by the experiment appear in the experiment's **ARTIFACTS** tab. ClearML automatically logs and tracks models
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Models created by the task appear in the task's **ARTIFACTS** tab. ClearML automatically logs and tracks models
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created using Keras.
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The experiment info panel shows model tracking, including the model name and design in **ARTIFACTS** **>** **Output Model**.
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The task info panel shows model tracking, including the model name and design in **ARTIFACTS** **>** **Output Model**.
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@@ -16,7 +16,7 @@ The example script does the following:
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dataset.
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1. Builds a sequential model using a categorical cross entropy loss objective function.
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1. Specifies accuracy as the metric, and uses two callbacks: a TensorBoard callback and a model checkpoint callback.
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1. During script execution, creates an experiment named `Keras with TensorBoard example` in the
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1. During script execution, creates a task named `Keras with TensorBoard example` in the
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`examples` project (in script) or the `Colab notebooks` project (in Jupyter Notebook).
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@@ -53,7 +53,7 @@ Text printed to the console for training progress, as well as all other console
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## Configuration Objects
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In the experiment code, a configuration dictionary is connected to the Task by calling [`Task.connect()`](../../../references/sdk/task.md#connect).
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A configuration dictionary is connected to the Task by calling [`Task.connect()`](../../../references/sdk/task.md#connect).
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```python
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task.connect_configuration(
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