Fix file extension, add redirections

Author: Orin-Thomas

.openpublishing.redirection.json

@@ -65149,6 +65149,16 @@
       "source_path": "learn-pr/azure/manage-secrets-with-azure-key-vault/7-summary.yml",
       "redirect_url": "/azure/security/",
       "redirect_document_id": false
+    }
+        {
+      "source_path": "learn-pr/tensorflow/intro-natural-language-processing-tensorflow/notebooks/2-represent-text-as-tensors.ipynb",
+      "redirect_url": "/azure/machine-learning/",
+      "redirect_document_id": false
+    },
+        {
+      "source_path": "learn-pr/tensorflow/intro-natural-language-processing-tensorflow/notebooks/3-embeddings.ipynb",
+      "redirect_url": "/azure/machine-learning",
+      "redirect_document_id": false
     }
   ]
 }

learn-pr/tensorflow/intro-natural-language-processing-tensorflow/includes/3-embeddings.md

@@ -176,7 +176,7 @@ To do that, we need to pretrain our embedding model on a large collection of tex
 
 CBoW is faster, and while skip-gram is slower, it does a better job of representing infrequent words.
 
-![Diagram showing both CBoW and Skip-Gram algorithms to convert words to vectors.](../media/example-algorithms-converting-words-vectors.png)
+![Diagram showing both CBoW and Skip-Gram algorithms to convert words to vectors.](../media/example-algorithms-converting-words-vectors.svg)
 
 To experiment with the Word2Vec embedding pretrained on Google News dataset, we can use the **gensim** library. Below we find the words most similar to 'neural'.