# Amazon — Preparing data for supervised fine-tuning Part 2: Advanced data strategies

- Company: Amazon (amazon.com)
- Announced: 2026-08-26T16:24:05+00:00
- Subject: Bedrock / Nova
- Models affected: Amazon Nova
- Source: https://aws.amazon.com/blogs/machine-learning/preparing-data-for-supervised-fine-tuning-part-2-advanced-data-strategies/
- Record: https://forck.live/items/4443-preparing-data-for-supervised-fine-tuning-part-2-advanced-data-strategies

The post is a guide on advanced data preparation strategies for supervised fine-tuning, covering learning curve analysis, data subset selection, augmentation, and mixing, with references to Amazon Nova customization findings. It is not a product or model announcement but a tutorial for practitioners.

## Evidence

Verbatim from https://aws.amazon.com/blogs/machine-learning/preparing-data-for-supervised-fine-tuning-part-2-advanced-data-strategies/:

> This second post covers four advanced strategies: evaluating data readiness with learning curve analysis, data subset selection and filtering, data augmentation, and data mixing.

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Record: https://forck.live/items/4443-preparing-data-for-supervised-fine-tuning-part-2-advanced-data-strategies
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