Add info about turning off auto-logging (#84)

docs/faq.md

@@ -378,12 +378,30 @@ After thirty minutes, it remains unchanged.
 
 **Can I control what ClearML automatically logs?** <a id="controlling_logging"></a>
 
-Yes! ClearML allows you to control automatic logging for `stdout`, `stderr`, and frameworks. 
+Yes! ClearML allows you to control automatic logging for `stdout`, `stderr`, and frameworks when initializing a Task
+by calling the [`Task.init`](references/sdk/task.md#taskinit) method. 
 
-When initializing a Task by calling the `Task.init` method, provide the `auto_connect_frameworks` parameter to control 
-framework logging, and the `auto_connect_streams` parameter to control `stdout`, `stderr`, and standard logging. The 
-values are `True`, `False`, and a dictionary for fine-grain control. See [Task.init](references/sdk/task.md#classmethod-initproject_namenone-task_namenone-task_typetasktypestraining-training-tagsnone-reuse_last_task_idtrue-continue_last_taskfalse-output_urinone-auto_connect_arg_parsertrue-auto_connect_frameworkstrue-auto_resource_monitoringtrue-auto_connect_streamstrue).
+To control a Task's framework logging, use the `auto_connect_framworks`. Turn off all automatic logging by setting the 
+parameter to `False`. For finer grained control of logged frameworks, input a dictionary, with framework-boolean pairs. 
 
+For example: 
+```python
+auto_connect_frameworks={
+    'matplotlib': True, 'tensorflow': False, 'tensorboard': False, 'pytorch': True,
+    'xgboost': False, 'scikit': True, 'fastai': True, 'lightgbm': False,
+    'hydra': True, 'detect_repository': True, 'tfdefines': True, 'joblib': True,
+}
+```
+
+To control the `stdout`, `stderr`, and standard logging, use the `auto_connect_streams` parameter. 
+To disable logging all three, set the parameter to `False`. For finer grained control, input a dictionary, where the keys are `stout`, `stderr`, 
+and `logging`, and the values are booleans. For example: 
+
+```python
+auto_connect_streams={'stdout': True, 'stderr': True, 'logging': False}
+```
+
+See [`Task.init`](references/sdk/task.md#taskinit).
 
 <br/>
 

docs/fundamentals/task.md

@@ -154,6 +154,9 @@ task = Task.init(
 )
 ```
 
+When a Task is initialized, it automatically captures parameters and outputs from supported frameworks. To control what ClearML
+automatically logs, see this [FAQ](../faq.md#controlling_logging).
+
 Once a Task is created, the Task object can be accessed from anywhere in the code by calling [`Task.current_task`](../references/sdk/task.md#taskcurrent_task).
 
 If multiple Tasks need to be created in the same process (for example, for logging multiple manual runs), 

docs/getting_started/ds/ds_first_steps.md

@@ -23,14 +23,16 @@ clearml-init
 
 In ClearML, experiments are organized as [Tasks](../../fundamentals/task). 
 
-ClearML will automatically log your experiment and code once you integrate the ClearML [SDK](../../clearml_sdk.md) with your code.
-At the beginning of your code, import the clearml package 
+ClearML will automatically log your experiment and code, including outputs and parameters from popular ML frameworks, 
+once you integrate the ClearML [SDK](../../clearml_sdk.md) with your code. To control what ClearML automatically logs, see this [FAQ](../../faq.md#controlling_logging). 
+
+At the beginning of your code, import the `clearml` package 
 
 ```python
 from clearml import Task
 ```
 
-:::note
+:::note Full Automatic Logging
 To ensure full automatic logging it is recommended to import the ClearML package at the top of your entry script.
 :::