Convolutional Neural Networks is one of the important topics when you are applying for jobs like AI/ML Engineer, Data Scientist (if it focuses on deep learning), Computer Vision Engineer, Deep Learning Researcher etc.

CNN-related questions are rare for junior-level positions but become essential for mid-to-senior roles. If someone is preparing for senior or mid-level job positions, you will definitely encounter these questions.

Junior Level Question

• How are CNNs used for Time Series Prediction?
• What's the difference between CNN and RNN and in which cases would use each one?

Mid-Level Question

• How CNN used in NLP?
• In CNN, what are the advantages and disadvantages of Max Pooling vs Average Pooling?
• What do the fully connected layers do in CNN's
• Name some advantages of using CNN vs DNN for image classification
• When should you use MLP, CNN, or RNN, and why?
• How is the Transformer Network better than CNNs and RNNs?
• Describe the architecture of a typical CNN

Senior Level Question

• What is intuition behind using CNN for NLP?
• Compare the CNN Multi-layer Perceptron
• What's the difference between multi-headed and multi-channel CNNs?
• What's the difference between Convolutional Layers vs Fully Connected Layers?
• What's the difference between CNN-LSTM's and ConvLSTMs?

These 15 questions cover the most frequently asked CNN topics in interviews. If you're aiming for a mid-to-senior AI/ML role, understanding these will help you stay ahead in technical discussions.

Thanks for reading,

Suraj…

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