MLS-C01 · Question #12
A company is observing low accuracy while training on the default built-in image classification algorithm in Amazon SageMaker. The Data Science team wants to use an Inception neural network…
The correct answer is C. Bundle a Docker container with TensorFlow Estimator loaded with an Inception network and use D. Use custom code in Amazon SageMaker with TensorFlow Estimator to load the model with an. https://aws.amazon.com/blogs/machine-learning/transfer-learning-for-custom-labels-using-a- tensorflow-container-and-bring-your-own-algorithm-in-amazon-sagemaker/
Question
A company is observing low accuracy while training on the default built-in image classification algorithm in Amazon SageMaker. The Data Science team wants to use an Inception neural network architecture instead of a ResNet architecture. Which of the following will accomplish this? (Choose two.)
Options
- ACustomize the built-in image classification algorithm to use Inception and use this for model
- BCreate a support case with the SageMaker team to change the default image classification
- CBundle a Docker container with TensorFlow Estimator loaded with an Inception network and use
- DUse custom code in Amazon SageMaker with TensorFlow Estimator to load the model with an
- EDownload and apt-get install the inception network code into an Amazon EC2 instance and use
How the community answered
(27 responses)- A4% (1)
- B4% (1)
- C81% (22)
- E11% (3)
Explanation
https://aws.amazon.com/blogs/machine-learning/transfer-learning-for-custom-labels-using-a- tensorflow-container-and-bring-your-own-algorithm-in-amazon-sagemaker/
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