Machine Learning Interviews

Chapter 3. Technical Interview: Machine Learning Algorithms

In Chapter 1, you learned about the various steps you will go through as part of your ML interviews. In Chapter 2, you looked at how to tie your experiences to roles of interest as well as how to craft a relevant resume. The goal of the previous chapters was to get you invited to interviews. In this chapter, I’ll focus on ML algorithms. As you recall, the interview process is illustrated in Figure 1-9, and the ML algorithms interview is only one portion of the technical interviews; the rest, such as ML training and evaluation, coding, and so on, will be covered in subsequent chapters.

Overview of the Machine Learning Algorithms Technical Interview

You’re likely to be asked ML algorithm technical questions in an interview if you’re applying for any of the following jobs:

• Data scientist who builds ML models

• Machine learning engineer

• Applied scientist

• And similar roles

Recall that within the common ML job titles (Figure 1-8), there are some jobs that have the responsibility of training ML models in the ML lifecycle. This chapter focuses on assessing candidates for those skills; if the job you’re aiming for focuses less on training ML models, you might get a simplified version of this type of interview, or it might be skipped completely.

This interview is meant to assess your understanding of ML algorithms, especially on the theoretical side. As to how you implement the algorithms with code, I cover that in the model deployment ...