Examtopics

Professional Machine Learning Engineer

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Topic 1 Question 10
Your team needs to build a model that predicts whether images contain a driver's license, passport, or credit card. The data engineering team already built the pipeline and generated a dataset composed of 10,000 images with driver's licenses, 1,000 images with passports, and 1,000 images with credit cards. You now have to train a model with the following label map: [˜drivers_license', ˜passport', `˜credit_card']. Which loss function should you use?
- Categorical hinge
- Binary cross-entropy
- Categorical cross-entropy
- Sparse categorical cross-entropy
解説
se sparse_categorical_crossentropy. Examples for above 3-class classification problem: [1] , [2], [3] Reference: https://stats.stackexchange.com/questions/326065/cross-entropy-vs-sparse-cross-entropy-when-to-use-one-over-the-other

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コメント(17)
- Answer is C
  
  👍 13
  ransev2021/06/24
- answer is D https://machinelearningmastery.com/how-to-choose-loss-functions-when-training-deep-learning-neural-networks/
  
  👍 8
  gcp2021go2021/06/07
- 正解だと思う選択肢: D
  answer is d
  
  👍 2
  MithunDesai2022/12/21
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