move francois to convolutional autoencode

autoencoder-classification.ipynb

@@ -861,7 +861,8 @@
    "source": [
     "We would hope and expect that a logistic regression model fit on an encoded version of the input to achieve better accuracy for the encoding to be considered useful. We can update the example to first encode the data using the encoder model trained in the previous section.\n",
     "\n",
-    "First, we can load the trained encoder model from the file. We can then use the encoder to transform the raw input data (e.g. 100 columns) into bottleneck vectors (e.g. 50 element vectors). This process can be applied to the train and test datasets."
+    "First, we can load the trained encoder model from the file. We can then use the encoder to transform the raw input data (e.g. 100 columns) into bottleneck vectors (e.g. 50 element vectors). This process can be applied to the train and test datasets.\n",
+    "![Illustrative Diagram on This Approach](2-layer-ae-LBGM.png)"
    ]
   },
   {