Approach a deep learning interview

Hello fast.ai alumnis,

I am enrolled in part 1 of the course, and have been focusing on deep learning and computer vision. Eventually I would like to secure a position of a Deep Learning Engineer.

I would like to know of your experiences of attending interviews for this kind of post.

How are these kind of interviews conducted? Is it all theory and your projects? Are you given to code? What would you recommend me to have as a final checklist of items to learn/brushup? What are the musts, and what can be ignored? (This is a vast area and though I am learning a lot, I will have to narrow down to revise.)

In short, how should one approach an deep learning interview?

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I think this is the best resource to refer to (by @rachel).

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Apologies, I feel a little bit bad about such a short answer and one that is slightly off-topic. You asked specifically about the interview, whereas the blog post I shared speaks to the broader question of how to navigate the field if you are approaching it without formal background or are in the process of building one.

I find this advice extremely valuable hence went ahead and shared, despite maybe it not being exactly what you were looking for. If that is the case, I do apologize.

All the best in your journey

Thanks @radek for sharing the link, it has valuable insights indeed!

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