Machine Learning System Design Interview

Product Information

Logistic regression. Try to implement logistic regression from scratch. Bonus point for vectorized version in numpy + completed in 20 minutes sample code from martinpella. Followup with MapReduce version.

Valerii: Well, I think that people can still find me on LinkedIn and find some questions there. ( 1:00:25) Alexey: [laughs] That’s cool. The question is about the book you mentioned – the book was Machine Learning Design Patterns, right? ( 52:56) Success” can be measured in numerous ways in machine learning system design. A successful machine learning system must gauge its performance by testing different scenarios. This can make a model’s design more innovative.The quality and quantity of training data is a big factor in determining how far you can go in your machine learning optimization task. Data collection techniques primarily involve user interactions, human labelers, or specialized labelers.

Valerii: These interviews are, of course, behavioral, project impact, (that makes sense, right?) and two very important things are the system design interview – which is how to design the system overall – and machine learning system design. These interviews are usually conducted for people starting from level five. Of course, at the very beginning nobody knows what level you are – it might be between four and five, so you might end up being level four, which is still common for this interview. ( 9:36) This interview question is designed to get signals on how good you are at applying ML/AI to real world applications.

team

There’s a lot of room for creativity here and you might be able to think of some options that are very application specific. Note that you can use more than one source! Infrastructure Alexey: Okay. If we take an ecommerce company – a small one – then we can think about what kind of questions they may ask candidates. It could be about designing a search system, designing a recommender system –the typical things that they do. However, when it comes to Facebook, Facebook does so many different things, so you can never know exactly what kind of domain you might get. They might ask you to design a newsfeed, for example. Or they might ask you to design a point of interest recommender system, or a fraud detection system for WhatsApp, right? It could be anything. ( 36:21) Valerii: Yeah, everybody – from a software engineer to a machine learning engineer. All these people go through system design. So that's why the audience, by definition, is larger. ( 34:56) Good understanding of machine learning algorithms (e.g. at least one of CS229, CS230, CS231N, CS224N