Don't remember exactly but it was a coding exercise involving grouping and finding intersections between items containing text fields. Wasn't too hard but I got stuck under the interview pressure.
Junior Machine Learning Engineer Interview Questions
6,580 junior machine learning engineer interview questions shared by candidates
Behavioral questions were heavily oriented towards the Amazon leadership qualities. > Name a time you were innovative > Name a time you delivered a simple solution to a complex problem. Follow up questions included how to quantify the level of success in projects brought up. Machine learning fundamentals: > How to deal with a troublesome dataset (interpretation open ended so think data cleaning, etc.) > How to deal with misrepresentative training data (imbalanced dataset, overfitting, explain how L1/L2 regularization work at an optimization level) > How to deal with a large dataset where only a few examples are labeled (semi-supervised learning) Coding question was: https://leetcode.com/problems/find-original-array-from-doubled-array/
HackerRank assessment included a variation of Leetcode's Shortest Path to Get Food problem
program k-nearest neighbour from draft
Describe an example where you had multiple alternatives to choose from for tools/approaches for a project. How did you go forward?
Predicting prices.
Google for examples of their silly questions.
optimization techniques (SMO, sgd, newton), momentum, saddle point good for sgd? , svm c change, conv or fcn layer has more memory ?
Describe normalization and bayes rule
Q. Solve the given coding problems.
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