Question 1

A financial services company wants to adopt Amazon SageMaker as its default data science environment. The company's data scientists run machine learning (ML) models on confidential financial dat

a. The company is worried about data egress and wants an ML engineer to secure the environment.

Which mechanisms can the ML engineer use to control data egress from SageMaker? (Choose three.)

Options :

A : Connect to SageMaker by using a VPC interface endpoint powered by AWS PrivateLink.

B : Use SCPs to restrict access to SageMaker.

C : Disable root access on the SageMaker notebook instances.

D : Enable network isolation for training jobs and models.

E : Restrict notebook presigned URLs to specific IPs used by the company.

F : Protect data with encryption at rest and in transit. Use AWS Key Management Service (AWS KMS) to manage encryption keys.

Answer: A,D,F

Question 2

The Chief Editor for a product catalog wants the Research and Development team to build a machine learning system that can be used to detect whether or not individuals in a collection of images are wearing the company's retail brand The team has a set of training data

Which machine learning algorithm should the researchers use that BEST meets their requirements?

Options :

A : Latent Dirichlet Allocation (LDA)

B : Recurrent neural network (RNN)

C : K-means

D : Convolutional neural network (CNN)

Answer: C

Question 3

A Machine Learning Specialist is building a convolutional neural network (CNN) that will classify 10 types of animals. The Specialist has built a series of layers in a neural network that will take an input image of an animal, pass it through a series of convolutional and pooling layers, and then finally pass it through a dense and fully connected layer with 10 nodes The Specialist would like to get an output from the neural network that is a probability distribution of how likely it is that the input image belongs to each of the 10 classes

Which function will produce the desired output?

Options :

A : Dropout

B : Smooth L1 loss

C : Softmax

D : Rectified linear units (ReLU)

Answer: C

Question 4

A healthcare company is using an Amazon SageMaker notebook instance to develop machine learning (ML) models. The company's data scientists will need to be able to access datasets stored in Amazon S3 to train the models. Due to regulatory requirements, access to the data from instances and services used for training must not be transmitted over the internet. Which combination of steps should an ML specialist take to provide this access? (Choose two.)

Options :

A : Configure the SageMaker notebook instance to be launched with a VPC attached and internet access disabled.

B : Create and configure a VPN tunnel between SageMaker and Amazon S3

C : Create and configure an S3 VPC endpoint Attach it to the VPC.

D : Create an S3 bucket policy that allows traffic from the VPC and denies traffic from the internet.

E : Deploy AWS Transit Gateway Attach the S3 bucket and the SageMaker instance to the gateway.

Answer: A,C

Question 5

A credit card company wants to identify fraudulent transactions in real time. A data scientist builds a machine

learning model for this purpose. The transactional data is captured and stored in Amazon S3. The historic data

is already labeled with two classes: fraud (positive) and fair transactions (negative). The data scientist removes

all the missing data and builds a classifier by using the XGBoost algorithm in Amazon SageMaker. The model

produces the following results:

True positive rate (TPR): 0.700

False negative rate (FNR): 0.300

True negative rate (TNR): 0.977

False positive rate (FPR): 0.023

Overall accuracy: 0.949

Which solution should the data scientist use to improve the performance of the model?

Options :

A :

Apply the Synthetic Minority Oversampling Technique (SMOTE) on the minority class in the training dataset. Retrain the model with the updated training data.

B :

Apply the Synthetic Minority Oversampling Technique (SMOTE) on the majority class in the training dataset. Retrain the model with the updated training data

C : Undersample the minority class

D : Oversample the majority class

Answer: A

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