updated teaser, added dividers
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@@ -9,6 +9,8 @@ by these solutions, and the trained network can give us predictions
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very quickly. There are a few important points to keep in mind when
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using supervised training.
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## Some things to keep in mind...
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### Natural starting point
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@@ -92,7 +94,7 @@ E.g., you'll notice that CNNs typically don't need dropout, as they're nicely
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regularized by construction. For MLPs, you typically need quite a bit to
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avoid overfitting.
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---
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## Supervised Training in a nutshell
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