Theoretical questions on Deep Learning and Neural Networks were asked followed by few CV based questions In one of my interview, they asked me to code few basic computer vision based code like "Write a code to find number of person entering a room and exiting a room" Few codes were asked on data analysis (using pandas library) At the end they asked me to code very basic Python code based on array, mostly to find average and sum of the array kind of question.
My interview was purely resume based. They asked me about my Machine Learning projects.
Deep Learning, GUI development, React.js and a bit on hardware
3 coding interviews, medium level leetcode - all related to image/matrix processing
Q: (Experience Specific). Could you tell me the thought process behind deciding on this model and how you evaluated it.
what would you do for 3d recognition? what tech you can use? base on images uploaded by user, how do you recommend furniture
What if your data/model assumptions were wrong for this project?
Technical and Behavioural Qs on your CV, projects and motivation. End-to-end system design, DB schema, Applied ML system design question.
Discussion/Questions around classical Computer Vision topics.
Started with an easy probability puzzle (ants in a triangle) Computer Vision - 1. Design a basic edge detection filter 2. Explain the whole SIFT pipeline. 3. How is SIFT made rotation invariant 4. Is HOG rotationally invariant Machine Learning - 1. Random Forest 2. XGBoost 3. ANNs 4. CNNs Focus is on fundamentals.
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