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Which technique can be used to improve model performance in terms of accuracy in the validation set?ī. This graph shows the training and validation loss against the epochs for a neural network.
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Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to train the full dataset. Confirm that the training code is executing and the model parameters seem reasonable. Load a smaller subset of the data into the SageMaker notebook and train locally.
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Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.ĭ. Use AWS Glue to train a model using a small subset of the data to confirm that the data will be compatible with Amazon SageMaker. Go back to Amazon SageMaker and train using the full datasetĬ. Train on a small amount of the data to verify the training code and hyperparameters. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to the instance. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.ī. Which approach allows the Specialist to use all the data to train the model?Ī. The Specialist wants to avoid loading all of this data onto an Amazon SageMaker notebook instance because it would take hours to move and will exceed the attached 5 GB Amazon EBS volume on the notebook instance. The dataset used to train this model is very large with millions of data points and is hosted in an Amazon S3 bucket. QUESTION 1 #Ī Machine Learning Specialist is developing a custom video recommendation model for an application. These questions are accurate for the test, and the review material is great. Secondly, Take An Online AWS MLS-C01 Practice TestĮxcept for Pass4itSure, I will not go to any other place for practice tests.
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