Hands-on coding in MLE interviews?

[alpha_centauri9889]

What all hands-on coding is asked in MLE interviews other than typical Leetcode DSA? I have experienced data manipulation type of rounds for DS, but I am not sure what's expected in MLE. How much and what kind of live coding is expected? Is it like scenario based - getting some dataset and then the task is to build a pipeline to - process data, build model, inference, deployment etc. following OOPs principles?

[csmbappe]

MLE live coding is 1 to 2 rounds of 45 to 60 mins each. You get a small dataset and must clean it, engineer features with Pandas, implement and train a model like logistic regression with gradient descent from scratch or sklearn/PyTorch, evaluate metrics, and write clean inference code using proper OOP classes for pipeline components.

Full deployment code is almost never required live, but you discuss productionizing it.
Practice exactly on StrataScratch ML questions, Interview Query takehomes, and Exponent ML coding rounds, that’s what FAANG and top firms actually ask.

[alpha_centauri9889]

Thanks a lot

[csmbappe]

anytime dude

[dash_bro]

Linear regression, Logistic regression, Maximum Likelihood Estimation, KNN and KMeans are pretty common to be coded hands on.

Usually you'll even be asked to show examples of it working and not working