Hi everyone,
I recently finished Part I as an international fellow. I’ve been looking for internships & entry level opportunities in the field and have a couple of interviews lined up. As someone whose knowledge of deep learning is limited to stuff I’ve learnt here in Fast.AI and 3 projects only with little to no theoretical knowledge, I’m wondering how to go about studying for these interviews.
What I’m looking to hear about:
- Was the material you learnt about in fast.ai enough to pass any interviews?
- Any resources you’d recommend besides the ones in the lesson wikis?
- Sometimes, the only justification I have for the models that I built in my projects is “it worked better than anything else I tried”. Is it okay to actually say this? I don’t think I can confidently defend every architecture decision I’ve made - this may be due to the lack of theoretical knowledge.
The projects I’ve done span across text data (LSTM), images (CNN), audio (CNN). I’ve read other posts here about interview prep. I have limited time (max 2 weeks) to study a lot and fill any gaps.
I’m looking forward to hearing from you all about any interviews you’ve done after fast.ai!
Thank you.