AWS-Certified-Machine-Learning-Specialty Free Practice Test

A company is setting up an Amazon SageMaker environment. The corporate data security policy does not allow communication over the internet.
How can the company enable the Amazon SageMaker service without enabling direct internet access to Amazon SageMaker notebook instances?

1. A. Create a NAT gateway within the corporate VPC.
2. B. Route Amazon SageMaker traffic through an on-premises network.
3. C. Create Amazon SageMaker VPC interface endpoints within the corporate VPC.
4. D. Create VPC peering with Amazon VPC hosting Amazon SageMaker.

Correct Answer: A

An e-commerce company needs a customized training model to classify images of its shirts and pants products The company needs a proof of concept in 2 to 3 days with good accuracy Which compute choice should the Machine Learning Specialist select to train and achieve good accuracy on the model quickly?

1. A. m5 4xlarge (general purpose)
2. B. r5.2xlarge (memory optimized)
3. C. p3.2xlarge (GPU accelerated computing)
4. D. p3 8xlarge (GPU accelerated computing)

Correct Answer: C

A machine learning specialist is running an Amazon SageMaker endpoint using the built-in object detection algorithm on a P3 instance for real-time predictions in a company's production application. When evaluating the model's resource utilization, the specialist notices that the model is using only a fraction of the GPU.
Which architecture changes would ensure that provisioned resources are being utilized effectively?

1. A. Redeploy the model as a batch transform job on an M5 instance.
2. B. Redeploy the model on an M5 instanc
3. C. Attach Amazon Elastic Inference to the instance.
4. D. Redeploy the model on a P3dn instance.
5. E. Deploy the model onto an Amazon Elastic Container Service (Amazon ECS) cluster using a P3 instance.

Correct Answer: B
https://aws.amazon.com/machine-learning/elastic-inference/

A company sells thousands of products on a public website and wants to automatically identify products with potential durability problems. The company has 1.000 reviews with date, star rating, review text, review summary, and customer email fields, but many reviews are incomplete and have empty fields. Each review has already been labeled with the correct durability result.
A machine learning specialist must train a model to identify reviews expressing concerns over product durability. The first model needs to be trained and ready to review in 2 days.
What is the MOST direct approach to solve this problem within 2 days?

1. A. Train a custom classifier by using Amazon Comprehend.
2. B. Build a recurrent neural network (RNN) in Amazon SageMaker by using Gluon and Apache MXNet.
3. C. Train a built-in BlazingText model using Word2Vec mode in Amazon SageMaker.
4. D. Use a built-in seq2seq model in Amazon SageMaker.

Correct Answer: B

A Machine Learning Specialist wants to determine the appropriate SageMakerVariant Invocations Per Instance setting for an endpoint automatic scaling configuration. The Specialist has performed a load test on a single instance and determined that peak requests per second (RPS) without service degradation is about 20 RPS As this is the first deployment, the Specialist intends to set the invocation safety factor to 0 5
Based on the stated parameters and given that the invocations per instance setting is measured on a per-minute basis, what should the Specialist set as the sageMakervariantinvocationsPerinstance setting?

1. A. 10
2. B. 30
3. C. 600
4. D. 2,400

Correct Answer: C