# <a name="depth"></a> 3. ML Depth
ML depth interviews typically aim to measure the depth of your knowledge in both theoretical and practical machine learning, in particular in the area that you claim you have worked on. Although this may sound scary at the beginning, this could be potentially one of the easiest rounds if you know well what you have worked on before. In other words, ML depth interviews typically focus on your previous ML related projects, but as deep as possible!

Typically these sessions start with going through one of your past projects (which depending on the company, it could be either your or the interviewer's choice). It generally starts as a high level discussion, and the interviewer gradually dives deeper in one or multiple aspects of the project, sometimes until you get stuck (so it's totally ok to get stuck, maybe just not too early!).

The best advice to prepare for this interview is to know the details of what you've worked on  before (really well), even if it goes back to several years ago.

**Examples:**

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