Overfitting - Wikipedia
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2026-07-16 09:16:37
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Text Highlight2026-07-16 15:40:37
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"Overfitting is especially likely in cases where learning was performed too long or where training examples are rare"
Whisper Note
Yeah that's why my model nails the test set but dies on new data, classic.
Text Highlight2026-07-16 12:37:37
Original Highlight Excerpt
"To lessen the chance or amount of overfitting, several techniques are available"
Whisper Note
But early stopping feels like a hack—sometimes it just masks a bad architecture.
Text Highlight2026-07-16 12:28:37
Original Highlight Excerpt
"To lessen the chance or amount of overfitting, several techniques are available"
Whisper Note
Regularization saved my models so many times, honestly a lifesaver.
Text Highlight2026-07-16 09:34:37
Original Highlight Excerpt
"overfitting is the production of an analysis that corresponds too closely or exactly to a particular set of data"
Whisper Note
I've seen this in my stock predictions—great past data, useless future calls.
Text Highlight2026-07-16 09:25:37
Original Highlight Excerpt
"overfitting is the production of an analysis that corresponds too closely or exactly to a particular set of data"
Whisper Note
Wait, isn't that just what happens when you try too hard to fit a line through every point?
Text Highlight2026-07-16 09:16:37
Original Highlight Excerpt
"overfitting is the production of an analysis that corresponds too closely or exactly to a particular set of data"
Whisper Note
So it's basically memorizing the test answers instead of learning the subject.
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