Edge devices Transformers YOLO (feature extractors, if YOLO uses grids, how would it be able to capture spatial data, how to process all the bounding boxes to get a single one i.e. non max suppression ) Difference between YOLO and R-CNN (and its faster variants) in terms of performance and speed. GPU optimization for trained model (important one which was asked in both interviews) - If I have a model that has 30 FPS on GPU, how would I tune it to get 50 or 60 FPS? Image matting - since my project revolved around it Types of convolutions Skip connections Difference between AlexNet and ResNet How to extract key value pairs from text using NLP
Deep Learning Engineer Interview Questions
286 deep learning engineer interview questions shared by candidates
Previous experience, machine learning theory, data management
Coding interview, level of difficulty: average question.
Coding interview, level of difficulty: average question.
Questions about my past projects, as well as related technical details about neural networks, model training and DL related questions. A question on maximum-likelihood. The second round is coding, asking me to write K-means and some optimizations with numpy operations.
What is your research philosophy?
Tell us bout Yourself ?
Explain the difference between a GAN and a VAE.
They asked about data structures.
1. Different ML algorithms with their use cases. Advantages and limitations of it. On-spot use case for deep learning model e.g. Table detection from images 2. Modeling pipeline for a DL model (image captioning). More focused on implementing the model architecture, and data pipeline, and a bit about deployment. Free to use the library documentation.
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