Name: Algorithm Coding Quality Tips
Uploaded: 2025-06-03T13:44:53+00:00
Duration: 1 min 26 s
Description: In this wrap-up of the ML algorithm coding interview section, we focus on what truly elevates our performance beyond jus

Algorithm Coding Quality Tips

In this wrap-up of the ML algorithm coding interview section, we focus on what truly elevates our performance beyond just getting a working implementation. Code quality, structure, and composure matter just as much as correctness.

- We should **structure our code clearly**, breaking it into logical methods like `fit`, `predict`, and `update_centroids` instead of writing one long script.
- **Clean abstractions** not only make our solution easier to understand, but also easier to debug and maintain—key traits of strong engineering.
- While full optimization isn’t expected, we must **show awareness of time and space complexity**, and briefly discuss trade-offs where relevant.
- If time allows, we should include **test cases using toy data**, showing that we think like engineers who validate their code.
- If our code breaks, we demonstrate a **calm, methodical debugging mindset**, which interviewers value as highly as technical correctness.

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In this wrap-up of the ML algorithm coding interview section, we focus on what truly elevates our performance beyond jus