Feat: add new Markdown parser (#39800)

and change all the challenges to new `md` format.

curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/deep-learning-demystified.md

@@ -5,30 +5,29 @@ challengeType: 11
 videoId: bejQ-W9BGJg
 ---
 
-## Description
+# --question--
 
-<section id='description'>
-</section>
+## --text--
 
-## Tests
+How should you assign weights to input neurons before training your network for the first time?
 
-<section id='tests'>
+## --answers--
 
-```yml
-question:
-  text: |
-    How should you assign weights to input neurons before training your network for the first time?
+From smallest to largest.
 
-  answers:
-    - |
-      From smallest to largest.
-    - |
-      Completely randomly.
-    - |
-      Alphabetically.
-    - |
-      None of the above.
-  solution: 2
-```
+---
+
+Completely randomly.
+
+---
+
+Alphabetically.
+
+---
+
+None of the above.
+
+## --video-solution--
+
+2
 
-</section>

curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/how-convolutional-neural-networks-work.md

@@ -5,28 +5,25 @@ challengeType: 11
 videoId: Y5M7KH4A4n4
 ---
 
-## Description
+# --question--
 
-<section id='description'>
-</section>
+## --text--
 
-## Tests
+When are Convolutional Neural Networks not useful?
 
-<section id='tests'>
+## --answers--
 
-```yml
-question:
-  text: |
-    When are Convolutional Neural Networks not useful?
+If your data can't be made to look like an image, or if you can rearrange elements of your data and it's still just as useful.
 
-  answers:
-    - |
-      If your data can't be made to look like an image, or if you can rearrange elements of your data and it's still just as useful.
-    - |
-      If your data is made up of different 2D or 3D images.
-    - |
-      If your data is text or sound based.
-  solution: 1
-```
+---
+
+If your data is made up of different 2D or 3D images.
+
+---
+
+If your data is text or sound based.
+
+## --video-solution--
+
+1
 
-</section>

curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/how-deep-neural-networks-work.md

@@ -5,28 +5,25 @@ challengeType: 11
 videoId: zvalnHWGtx4
 ---
 
-## Description
+# --question--
 
-<section id='description'>
-</section>
+## --text--
 
-## Tests
+Why is it better to calculate the gradient (slope) directly rather than numerically?
 
-<section id='tests'>
+## --answers--
 
-```yml
-question:
-  text: |
-    Why is it better to calculate the gradient (slope) directly rather than numerically?
+It is computationally expensive to go back through the entire neural network and adjust the weights for each layer of the neural network.
 
-  answers:
-    - |
-      It is computationally expensive to go back through the entire neural network and adjust the weights for each layer of the neural network.
-    - |
-      It is more accurate.
-    - |
-      There is no difference between the two methods.
-  solution: 1
-```
+---
+
+It is more accurate.
+
+---
+
+There is no difference between the two methods.
+
+## --video-solution--
+
+1
 
-</section>

curriculum/challenges/english/11-machine-learning-with-python/how-neural-networks-work/recurrent-neural-networks-rnn-and-long-short-term-memory-lstm.md

@@ -5,28 +5,25 @@ challengeType: 11
 videoId: UVimlsy9eW0
 ---
 
-## Description
+# --question--
 
-<section id='description'>
-</section>
+## --text--
 
-## Tests
+What are the main neural network components that make up a Long Short Term Memory network?
 
-<section id='tests'>
+## --answers--
 
-```yml
-question:
-  text: |
-    What are the main neural network components that make up a Long Short Term Memory network?
+New information and prediction.
 
-  answers:
-    - |
-      New information and prediction.
-    - |
-      Prediction, collected possibilities, and selection.
-    - |
-      Prediction, ignoring, forgetting, and selection.
-  solution: 3
-```
+---
+
+Prediction, collected possibilities, and selection.
+
+---
+
+Prediction, ignoring, forgetting, and selection.
+
+## --video-solution--
+
+3
 
-</section>