딥러닝 면접 질문 모음 (Shlomo Kashani 책 레퍼런스)
https://arxiv.org/pdf/2201.00650.pdf
책의 목표
- 석사/박사를 막 졸업한 학생들이 취직을 할 때 보게되는 딥러닝 관련 기술면접 질문들 모음
- 혼자 공부할 때도 굉장히 좋을 듯
목차
- 난이도: 어린이집
- Logistic regression
- 예시 - Sigmoid, Logit function & entropy
- Probabilistic programming & Bayesian DL
- 예시 - Expectation & variance, Bayes rule, Maximum Likelihood estimation
- Logistic regression
- 난이도: 고등학교
- Information theory
- 예시 - Shannon’s entropy, KL Divergence
- Deep Learning: Calculus, Algorithmic differentitation
- 예시 - Gradient descent & Backpropagation, Partial derivatives, Activation functions
- Information theory
- 난이도: 학부생
- Deep Learning: NN Ensembles
- 예시 - Bagging / Boosting / Stacking, Snapshot Ensembling, Multi-model Ensembling
- Deep Learning: CNN feature extraction
- 예시 - Fine-tuning CNNs, Neural Style transfer
- Deep Learning
- 예시 - Convolution and correlation, Training & hyperparameters, Optimization & loss
- Deep Learning: NN Ensembles
- Mock exam