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# Machine Learning and Human Learning

**[Medium](https://daily.dev/sources/medium_js)** · 2 min read · 0 upvotes · 0 comments

## Summary

A philosophical reflection drawing parallels between how machines learn from data and how humans learn from experiences. The core analogy: just as ML models reflect the quality and nature of their training data, humans reflect the people, books, and media they engage with. Key points include the importance of starting with a clear problem statement, choosing appropriate models/approaches, and treating life like an ML feedback loop — experiment, analyze, self-correct, and improve.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/@savitha.vijayarangan09/machine-learning-and-human-learning-f02a1dc65f89>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#data-quality](https://daily.dev/tags/data-quality)

[View this post on daily.dev](https://daily.dev/posts/machine-learning-and-human-learning-n1duxewun)

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