The effect of learning rate initialization and batch size on cnn
Learning Engineer Interview Questions
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1. Expression Tree given as input. Evaluate the expression. 2. Counting the number of ways to climb a ladder. 3. A problem on Template Matching - Computer Vision. 4. Few Machine Learning Concepts - explaining algorithms. 5. Many Deep Learning Concepts - explaining the details on how training is done. 6. Coin change problem. 7. Resume based questions and was ask to code an algorithm implemented in one of my projects.
Why interest in working at Nvidia
How do you know about diffusion model?
a dynamic programming coding question
Background check nothing to add
Talk about your resume, brief history, Pick your favorite ML project and go into detail from the beginning, the interviewer will ask questions as you are explaining, so do not wait for them to ask you to start.
Code Design Round: The question was something similar to the following: Let’s pretend we are in charge of a cinema. We want to figure out whether a new movie can be added to the existing schedule without removing any of the current movies. Note that: the cinema opens at 10:00 the last possible end time for a movie is 23:00 movie durations include setting up the room before the movie begins and cleaning it up afterward. In other words, if for example a movie ends at 14:00, the next movie can start at 14:00 movie start times are expressed in minutes starting from midnight, so for example, 10am would be 10*60 = 600
1st Interview: what is RAG why do we use it and metadata filtering. Fairly easy ones. Then asked me coding leetcode easy/medium level question on live coding. 2nd Interview:Design a recommendation system for a store when the input is an api with only userid. He then asked a medium/hard leetcode level coding question.
1. Machine learning and deep learning questions, like bias vs variance, parallel mini batch training. 2. Cuda optimization questions
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