Machine Learning Interview

Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog:
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Minimum Viable Study Plan for Machine Learning Interviews

Machine Learning System Design - Early Preview - Buy on Amazon
Machine Learning System Design Interview

Machine Learning interviews book on Amazon.
Machine Learning Interviews book on Amazon

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Machine Learning Design

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3. LinkedIn Feed Ranking LinkedIn Feed Ranking
4. Ad Click Prediction Ad Click Prediction
5. Estimate Delivery time Estimate Delivery time
6. Airbnb Search ranking Airbnb Search ranking

Getting Started

How to Resources
List of promising companies WealthFront 2021 list.
Prepare for interview Common questions about Machine Learning Interview process.
Study guide Study guide contained minimum set of focus area to aces your interview.
Design ML system ML system design includes actual ML system design usecases.
ML usecases ML usecases from top companies
Test your ML knowledge Machine Learning quiz are designed based on actual interview questions from dozen of big companies.
One week before onsite interview Read one week check list
How to get offer? Read success stories
FAANG companies actual MLE interviews Read interview stories
Practice coding Leetcode questions by categories for MLE
Advance topics Read advance topics

Study guide

LeetCode (not all companies ask Leetcode questions)

  • NOTE: there are a lot of companies that do NOT ask leetcode questions. There are many paths to become an MLE, you can create your own path if you feel like leetcoding is a waste of time.

  • I use LC time tracking to keep track of how many times I solves a question and how long I spent each time. Once I finish non-trivial medium LC questions 3 times, I have absolutely no issues solving them in actual interviews (sometimes within 8-10 minutes). It makes a big difference. A better way is to use LeetPlug chrome extension here

Leetcode questions by categories



Statistics and probability

  • The only cheatsheet that you''ll ever need

  • Learn Bayesian and practice problems in Bayesian
  • Let A and B be events on the same sample space, with P (A) = 0.6 and P (B) = 0.7. Can these two events be disjoint?
  • Given that Alice has 2 kids, at least one of which is a girl, what is the probability that both kids are girls? (credit swierdo)
  • A group of 60 students is randomly split into 3 classes of equal size. All partitions are equally likely. Jack and Jill are two students belonging to that group. What is the probability that Jack and Jill will end up in the same class?
  • Given an unfair coin with the probability of heads not equal to .5. What algorithm could you use to create a list of random 1s and 0s.

Big data (NOT required for Google, Facebook interview)

ML fundamentals

AB testing

DL fundamentals

ML system design

ML classic paper

ML productions

Food delivery

ML design common usecases

Fraud detection (TBD)




  • V, Amazon L5 DS

I really found the quizzes very helpful for testing my ML understanding. Also, the resources shared helped me a lot for revising concepts for my interview preparation. This course will definitely help engineers crack Machine Learning Engineering and Data Science interviews.

  • K, Facebook MLE

I really like what you've built, it'll help a lot of engineers.


I have been using your github repo to prep for my interviews and got an offer with NVIDIA with their data science team. Thanks again for your help!

  • A, Booking

Woow this is very useful summaries, so nice.

  • H, Microsoft

That's incredible!

  • V, Intel

The repo is extremely cohesive! Thanks again.


  • This repo is written based on REAL interview questions from big companies and the study materials are based on legit experts i.e Andrew Ng, Yoshua Bengio etc.

  • I have 6 YOE in Machine Learning and have interviewed more than dozen big companies. This is the minimum viable study plan that covers all actual interview questions from Facebook, Amazon, Apple, Google, MS, SnapChat, Linkedin etc.

  • If you're interested to learn more about paid ML system design course, click here. This course will provide 6-7 practical usecases with proven solutions. After this course you will be able to solve new problem with systematic approach.

Acknowledgements and contributing

  1. Thanks for early feedbacks and contributions from Vivian, aragorn87 and others. You can create an Issue or Pull Request on this repo. You can also help upvote on ProductHunt

  2. If you find this helpful, you can Sponsor this project. It's cool if you don't.

  3. Thanks to this community, we have donated about $200 to HopeForPaws. If you want to support, you can contribute too on their website.

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