Describe overfitting, describe batch nromalization, what is the difference between classification and regression, how to implement grid search
Deep Learning Research Engineer Interview Questions
168 deep learning research engineer interview questions shared by candidates
What relevant projects have you tackled with regards to the position that you are applying for?
Asked about my research experience and how I would apply my research to their engineering problems.
How the foundation models can be applied to an intelligent voice system.
KPI metrics, relevant coding experience, neural network architecture, image processing, object detection, segmentation
They asked general question about deep neural networks, what is convolution, what is a conv layer, do i know specific networks and their architectures. Than a short english talking part to measure my english level.
What are the layers of a neural network? and what do they do? There are also two computational questions about CNN's.
Projects Contribution in each project Guesstimates Knowledge on ML concepts and application
Tensor Flow, About Dropouts, Model Training AWS use case -- with TWO faces and how to Detect the Face...AWS Beanstalk, AWS DynamoDB.... Computer Vision --- More about the works and Model Training, Metrics used, False Positive, False Negative....
what's the function of back normalization?
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