Hi Leetcoders,
I am preparing for a ML role and in my past interviews I have often realised that questions like 'build a sentiment analysis for comments dataset' or 'recommendation system for hotels/music/movies' or 'search recommendation system' etc etc get asked. Now I consider my self to have decent knowledge of these topics but I find it difficult to explain it in interviews. I get confused in things like where to start from and what to discuss or focus on? There can be lot of things like where can you get your data from or which model to use or metrics or preprocessing techniques. I am looking for question specific guides which I couldn't find myself. Guides that pick a statement (like a hotel recommendation system for swiggy) and has everything that needs to be discussed in interview (in appropriate depth). I'm not looking for generic articles explaining all problems as a 5 step approach.

Note: I don't really want to memorise stuff by reading articles. Deep learning has various applications and most of them are quite different from each others. I want to use these articles to know a bit about all the use cases and mostly, to learn to organise my thoughts using these case studies as examples.

It will be really great if this thread can serve as collection of good articles on different topics.

Frankly, if I can get answer to these questions in this open-source GitHub book https://huyenchip.com/machine-learning-systems-design/exercises.html#exercises-rWl8SQW , that's all I will need. Sadly, I couldn't find them and doubt if they exist.

Please upvote this thread if you think you will be interested in such a resource.