add another example, fix location in Readme.md

openml · Nov 6, 2024 · 1511e16 · 1511e16
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diff --git a/README.md b/README.md
@@ -47,7 +47,7 @@ print('URL for run: %s/run/%d' % (openml.config.server, run.run_id))
 
 ```
 
-Note: The input layer of the network should be compatible with OpenML data output shape. Please check [examples](/examples/) for more information.
+Note: The input layer of the network should be compatible with OpenML data output shape. Please check [examples](/docs/Examples/) for more information.
 
 
 Additionally, if you want to publish the run with onnx file, then you must call ```openml_pytorch.add_onnx_to_run()``` immediately before ```run.publish()```. 

diff --git a/examples/tf_transfer_learning.py → docs/Examples/tf_transfer_learning.py b/examples/tf_transfer_learning.py → docs/Examples/tf_transfer_learning.py
@@ -2,7 +2,9 @@
 Tensorflow image classification using pre-trained model example
 ==================
 
-An example of a tensorflow network that classifies indoor scenes images.
+An example of a tensorflow pre-trained network that classifies indoor scenes images, where all layers are trained. 
+For smaller datasets or datasets similar to the dataset the base model was trained on, 
+it is advisable to freeze pre-trained network, and only train custom layers. 
 """
 
 import openml

diff --git a/docs/index.md b/docs/index.md
@@ -47,7 +47,7 @@ print('URL for run: %s/run/%d' % (openml.config.server, run.run_id))
 
 ```
 
-Note: The input layer of the network should be compatible with OpenML data output shape. Please check [examples](/examples/) for more information.
+Note: The input layer of the network should be compatible with OpenML data output shape. Please check [examples](/docs/Examples/) for more information.
 
 
 Additionally, if you want to publish the run with onnx file, then you must call ```openml_pytorch.add_onnx_to_run()``` immediately before ```run.publish()```. 

diff --git a/mkdocs.yml b/mkdocs.yml
@@ -62,5 +62,6 @@ nav:
     - "Performance Check Image Classification Task": "Examples/tf_image_classification_sanity_check.py"
     - "Image Classification Task on Big Dataset": "Examples/tf_image_classification_Indoorscenes_dataset.py"
     - "Pretrained Image Classification Example": "Examples/tf_pretrained_model_Indoorscenes_dataset.py"
+    - "Pretrained Image Classification on Big Dataset": "Examples/tf_transfer_learning.py"
   # - "Limitations of the API":  "Limitations of the API.md"