You work as a machine learning specialist for a sports gambling website. Your machine learning team has been asked to create a football score prediction model that predicts the winner of a match, the score difference, and the shots-on-goal differential. You have collected historical football match data, and you have selected the SageMaker XGBoost built-in algorithm to use for your model. You are now ready to train your model using a SageMaker training job. Which of the following are NOT used by your SageMaker training job? (Select TWO)

Answer options:

A.URL of the S3 bucket where you have stored your training data
B.SageMaker managed ML compute instances that SageMaker will use for model training
C.ECS path where the training code is stored
D.URL of the S3 bucket where you have stored your training code
E.ECR path where the training code is stored

Correct Answers: C and D
Option A is incorrect. You must supply the URL of the S3 bucket where you have stored your training data to run your training job.
Option B is incorrect. You must supply the ML compute instances that SageMaker will use for model training.
Option C is correct. Your training code is referenced by an ECR path to your training code, not an ECS path.
Option D is correct. Your training code is referenced by an ECR path to your training code, not the URL of an S3 bucket.
Option E is incorrect. You must supply the ECR path where the training code is stored for your training job to use.
References:
Please see the Amazon SageMaker developer guide titled Train a Model with Amazon SageMaker (https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works-training.html),
The Amazon SageMaker developer guide titled Docker Registry Paths for SageMaker Built-in Algorithms (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html)