Monty Hall scenario with 100 options rather than 3 doors, once you see one you can’t go back. First level was set a threshold where you didn't need the max. Second level was now you want the max so use chance and odds probability rather than statistics reasoning. Be careful. Interviewer did not have subject matter expertise. Feedback was that keeping her taught/mentored during the process and comfortable was more important that solving the problem well.
they were asking me about R-squared
How to use pandas for EDA.
first OA -> 1 easy dsa questions first interview round -> 2 easy-medium dsa questions second interview -> focused on machine learning and mainly on mathematics and derivations.
many behavioral and LP questions, and some questions related to my research and experience.
Machine Learning Basics, SQL, Leadership questions, Behavioral questions
I was asked more than 50 questions, from basic classifiers (SVM, Decision trees) all the way to Transformers, VAEs, etc. Then, I was asked how would I improve Alexa to generate speech with emotions.
Online Assessment: 2 LeetCode easy-medium questions with a 70 min time limit Round 1: -Asked about a recent research project on my resume. - Asked some basic computer vision questions: -- How does ResNEt work? -- Define the metric IOU -- What is the difference between Instance segmentation and semantic segmentation? -- How would you find the location of an object in 3D space with stereo cameras? Round 2: - Drill down on a previous interview experience - Asked basic questions about metrics used in computer vision (mAP, IoU, etc) - System design question -- Design a high level robot system that can identify books and place them on the shelf.
First round: coding. Basic DS & algo questions Second: Deep dive into past projects and basic ML questions on overfitting, bias/variance, etc
Leadership Principles, SQL Query, LC Medium
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