system design for ads filtering system
Applied Scientist Interview Questions
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ML basics, NLP, Leetcode, behavioral
* ML Basics, Past projects walk through, DSA
First interview about big data and OLS
Real project about zalando, ML/AI
Tell me about yourself and relevant projects for this role
One 90 minutes technical screening with questions on statistics, applied deep learning, machine learning theory and a easy coding question on TF-IDF Got opportunity to do onsite interview. 5 rounds total Round 1: ML depth, the interviewer simply took the problem he worked on in zalando, forecasting and marketing intelligence. I.e. modelling the bidding of Google keywords during search for placing their ads to users. I had no experience with reinforcement learning, he expected multi arm bandit solution. Round2: Research chat with Director of Casual inference team. This was chat with director of different team to see scientific thinking. Overall went well imo. Round3: Coding round, had a dynamic programming / recursion question where i had to break strings in given set into smaller strings based on reference set. Eg: if reference set has {pan, cake} then break pancake in main set to {pancake : [pan, cake]} Was able to code the solution and interviewer was quite happy with solution. Round 4: Hiring manager round, it had mostly behavioural questions judging team skills in techincal scenarios. Also questions on how do I structure, test and review my code. Round 5: HR round, non technical behavioural round. Went well. Overall feedback: Coding excellent, ML stat ok however this is senior position and needs more experience. Very diplomatic feedback from the process that i don't appreciate.
Describe tools and skills to solve overfitting?
Explain Machine Learning algorithms like Kmeans clustering , Linear regression and algos specific to predictive modelling . How to choose no of clusters in K means
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