Update docs for ClearML server 1.6 (#280)

docs/guides/frameworks/keras/jupyter.md

@@ -29,8 +29,6 @@ They appear in **PLOTS**.
 
 ![image](../../../img/examples_keras_jupyter_03a.png)
 
-![image](../../../img/examples_keras_jupyter_03b.png)
-
 ## Debug Samples
 
 The example calls Matplotlib methods to log debug sample images. They appear in **DEBUG SAMPLES**.

docs/guides/frameworks/keras/keras_tensorboard.md

@@ -57,9 +57,12 @@ In the experiment code, a configuration dictionary is connected to the Task by c
 method. 
 
 ```python
-task.connect_configuration({'test': 1337, 'nested': {'key': 'value', 'number': 1}})
+task.connect_configuration(
+   name="MyConfig" 
+   configuration={'test': 1337, 'nested': {'key': 'value', 'number': 1}}
+)
 ```
 
-It appears in **CONFIGURATION** **>** **CONFIGURATION OBJECTS** **>** **General**. 
+It appears in **CONFIGURATION** **>** **CONFIGURATION OBJECTS** **>** **MyConfig**. 
 
 ![image](../../../img/keras_colab_02.png)

docs/guides/frameworks/pytorch_ignite/pytorch_ignite_mnist.md

@@ -159,10 +159,6 @@ View the scalars, including training and validation metrics, in the experiment's
 
 ![image](../../../img/ignite_training.png)
 
-<br/>
-
-![image](../../../img/ignite_validation.png)
-
 ### Model Snapshots
  
 

docs/guides/frameworks/xgboost/xgboost_sample.md

@@ -18,7 +18,10 @@ classification dataset using XGBoost
 The feature importance plot and tree plot appear in the project's page in the **ClearML web UI**, under 
 **PLOTS**.
 
-![image](../../../img/examples_xgboost_sample_06.png)
+![Feature importance plot](../../../img/examples_xgboost_sample_06.png)
+
+![Tree plot](../../../img/examples_xgboost_sample_06a.png)
+
 
 ## Console