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How much data are sufficient to train my machine learning model?

The "Rule of Ten" might work okay for some problems (e.g. linear, or a known functional form). This is NOT a general rule. All we need is one counter-example to show that this is not a ...
Andrew Speendtr's user avatar
1 vote

Reducing emails token count preprocessing for Large Email Datasets - Feeding LLMs

Instead of the approaches you mentioned, I suggest a completely different approach: a retrieval-augmented generation (RAG) system. I am doing this because what you described is a typical use case for ...
noe's user avatar
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Missing data in train set and test set

Generally speaking, any missing values you find in the data you want to predict (unseen data or test data) should be handled the same way you handled in the training data. For example, in your ...
alepfu's user avatar
  • 11

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