Name: Code Quality
Uploaded: 2025-06-03T12:59:40+00:00
Duration: 2 min
Description: In this section, we focus on code quality, a crucial yet often underestimated element of ML interviews

Code Quality

In this section, we focus on **code quality**, a crucial yet often underestimated element of ML interviews. Even if our model works well, poorly written code can seriously damage our impression. Clean, clear code reflects professional maturity and real-world readiness.

- **Mediocre code** may be functional but is hard to read—characterized by cryptic variable names, long repetitive functions, unclear logic, and little to no documentation.
- **Stellar candidates write clean, organized code**, breaking it into logical chunks with reusable functions and clearly labeled sections.
- We use **meaningful variable names**, write comments that explain the "why" behind decisions, and maintain a logical flow from start to finish.
- Our code is **efficient in design**, avoiding unnecessary complexity and maintaining smooth execution without over-optimizing.
- Ultimately, we recognize that **code is communication**—and polished, maintainable code signals we’re ready to contribute to real engineering teams.

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In this section, we focus on code quality, a crucial yet often underestimated element of ML interviews

Anybody can write code, but few can write truly good code. Code quality is arguably the biggest differentiator when it comes the market value and impact of a software engineer.

Tech has one of the highest rates of job switching, making this skill incredibly high-leverage and vital to master. Understand what it takes to convince companies you are strongly competent.