Interview resources : ML/Data Science/AI Research Engineer

Interviewing is a grueling process, specially during COVID. I recently interviewed with Microsoft (Data Scientist ll), Amazon (Applied AI Scientist) and Apple (Software Development : Machine Learning).

Though all these interviews differed a bit, but the basic questions asked were the same. During the process I curated this list which would help you pass all ML interviews.

NOTE : This list is just for end moment revising

Machine Learning

Linear, Logistic regression-

Naive Bayes-

SVM / Kernel-

Random Forests, decision Trees, Boosting, Bagging, Xgboost- StatQuest Youtube videos

EM Algorithm-

K means-

K nearest neighbors-

Evaluation Metrics (scroll to the definition section, you need to know the confusion metrics, precision, recall, type I, type II, FP rate, sensitivity)-

Regularization (L1,L2, Why is L1 sparse?)

Bias Variance Trade off

Dimensionality Reduction-

Deep Learning

The first thing I would suggest to do is to go through all the courses which is pretty basic. If someone already publishes/ works in these topics they might just skip watching all the videos and can go through the following questions/ resources-


For NLP CS224 (5) Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 1 — Introduction and Word Vectors — YouTube) covers the basics of NLP with Deep Learning. This might cover 3/4 of the questions asked in an interview. Other questions are usually more state of the art models as the interviewer wants to check how updated you are.

Other topics —

  1. Linear Algebra-
  2. Probability basics-
  3. Stats- I had taken a graduate level Statistics class so I didnt need to brush this up but Khan Academy is a very good source for learning basics with examples.

These are the topics which are asked in all interviews, obvious then some questions were specific to research I had done. There were also live coding rounds both of algorithms and NN models. Let me know if I missed something.



Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store