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title: Solving the Human Training Data Problem | daily.dev
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> ## Documentation Index
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> Use this file to discover all available pages before exploring further.

# Solving the Human Training Data Problem

**[Towards Data Science](https://daily.dev/sources/tds)** · 17 min read · 1 upvotes · 0 comments

## Summary

A graduate student shares how they used Claude to generate synthetic practice exams when real past exams weren't available at their new university. Drawing a parallel between machine learning concepts (synthetic data, overfitting, dataset pollution) and human studying, the author describes two scenarios: replicating a known exam template and constructing mock exams from scratch. About 60% of questions on the actual exam matched their practice material, but a blind spot emerged from over-relying on personal assumptions about what would be tested. Key lessons include using separate chat sessions to avoid context rot, keeping an open mind about edge-case topics, and supplementing synthetic data with real exam questions when possible. The piece concludes with a broader reflection on LLMs as learning tools that can personalize education when used responsibly.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/solving-the-human-training-data-problem/>

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---

Tags: [#llm](https://daily.dev/tags/llm), [#claude](https://daily.dev/tags/claude)

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