NEW QUESTION 1
A Machine Learning Specialist deployed a model that provides product recommendations on a company's website Initially, the model was performing very well and resulted in customers buying more products on average However within the past few months the Specialist has noticed that the effect of product recommendations has diminished and customers are starting to return to their original habits of spending less The Specialist is unsure of what happened, as the model has not changed from its initial deployment over a year ago
Which method should the Specialist try to improve model performance?

• A. The model needs to be completely re-engineered because it is unable to handle product inventory changes
• B. The model's hyperparameters should be periodically updated to prevent drift
• C. The model should be periodically retrained from scratch using the original data while adding a regularization term to handle product inventory changes
• D. The model should be periodically retrained using the original training data plus new data as product inventory changes

Answer: D

NEW QUESTION 2
A Machine Learning Specialist at a company sensitive to security is preparing a dataset for model training. The dataset is stored in Amazon S3 and contains Personally Identifiable Information (Pll). The dataset:
* Must be accessible from a VPC only.
* Must not traverse the public internet. How can these requirements be satisfied?

• A. Create a VPC endpoint and apply a bucket access policy that restricts access to the given VPC endpoint and the VPC.
• B. Create a VPC endpoint and apply a bucket access policy that allows access from the given VPC endpoint and an Amazon EC2 instance.
• C. Create a VPC endpoint and use Network Access Control Lists (NACLs) to allow traffic between only the given VPC endpoint and an Amazon EC2 instance.
• D. Create a VPC endpoint and use security groups to restrict access to the given VPC endpoint and an Amazon EC2 instance.

Answer: B

NEW 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?

• A. Dropout
• B. Smooth L1 loss
• C. Softmax
• D. Rectified linear units (ReLU)

Answer: D

NEW QUESTION 4
A large mobile network operating company is building a machine learning model to predict customers who are likely to unsubscribe from the service. The company plans to offer an incentive for these customers as the cost of churn is far greater than the cost of the incentive.
The model produces the following confusion matrix after evaluating on a test dataset of 100 customers: Based on the model evaluation results, why is this a viable model for production?

• A. The model is 86% accurate and the cost incurred by the company as a result of false negatives is less than the false positives.
• B. The precision of the model is 86%, which is less than the accuracy of the model.
• C. The model is 86% accurate and the cost incurred by the company as a result of false positives is less than the false negatives.
• D. The precision of the model is 86%, which is greater than the accuracy of the model.

Answer: B

NEW QUESTION 5
A Data Science team is designing a dataset repository where it will store a large amount of training data commonly used in its machine learning models. As Data Scientists may create an arbitrary number of new datasets every day the solution has to scale automatically and be cost-effective. Also, it must be possible to explore the data using SQL.
Which storage scheme is MOST adapted to this scenario?

• A. Store datasets as files in Amazon S3.
• B. Store datasets as files in an Amazon EBS volume attached to an Amazon EC2 instance.
• C. Store datasets as tables in a multi-node Amazon Redshift cluster.
• D. Store datasets as global tables in Amazon DynamoDB.

Answer: A

NEW QUESTION 6
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?

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

Answer: A

NEW QUESTION 7
A Machine Learning Specialist is using Amazon SageMaker to host a model for a highly available customer-facing application .
The Specialist has trained a new version of the model, validated it with historical data, and now wants to deploy it to production To limit any risk of a negative customer experience, the Specialist wants to be able to monitor the model and roll it back, if needed
What is the SIMPLEST approach with the LEAST risk to deploy the model and roll it back, if needed?

• A. Create a SageMaker endpoint and configuration for the new model versio
• B. Redirect production traffic to the new endpoint by updating the client configuratio
• C. Revert traffic to the last version if the model does not perform as expected.
• D. Create a SageMaker endpoint and configuration for the new model versio
• E. Redirect production traffic to the new endpoint by using a load balancer Revert traffic to the last version if the model does not perform as expected.
• F. Update the existing SageMaker endpoint to use a new configuration that is weighted to send 5% of the traffic to the new varian
• G. Revert traffic to the last version by resetting the weights if the model does not perform as expected.
• H. Update the existing SageMaker endpoint to use a new configuration that is weighted to send 100% of the traffic to the new variant Revert traffic to the last version by resetting the weights if the model does not perform as expected.

Answer: A

NEW QUESTION 8
A Machine Learning Specialist is building a logistic regression model that will predict whether or not a person will order a pizza. The Specialist is trying to build the optimal model with an ideal classification threshold.
What model evaluation technique should the Specialist use to understand how different classification thresholds will impact the model's performance?

• A. Receiver operating characteristic (ROC) curve
• B. Misclassification rate
• C. Root Mean Square Error (RM&)
• D. L1 norm

Answer: A

NEW QUESTION 9
A Machine Learning Specialist is required to build a supervised image-recognition model to identify a cat. The ML Specialist performs some tests and records the following results for a neural network-based image classifier:
Total number of images available = 1,000 Test set images = 100 (constant test set)
The ML Specialist notices that, in over 75% of the misclassified images, the cats were held upside down by their owners.
Which techniques can be used by the ML Specialist to improve this specific test error?

• A. Increase the training data by adding variation in rotation for training images.
• B. Increase the number of epochs for model training.
• C. Increase the number of layers for the neural network.
• D. Increase the dropout rate for the second-to-last layer.

Answer: B

NEW QUESTION 10
A Machine Learning Specialist is designing a system for improving sales for a company. The objective is to use the large amount of information the company has on users' behavior and product preferences to predict which products users would like based on the users' similarity to other users.
What should the Specialist do to meet this objective?

• A. Build a content-based filtering recommendation engine with Apache Spark ML on Amazon EMR.
• B. Build a collaborative filtering recommendation engine with Apache Spark ML on Amazon EMR.
• C. Build a model-based filtering recommendation engine with Apache Spark ML on Amazon EMR.
• D. Build a combinative filtering recommendation engine with Apache Spark ML on Amazon EMR.

Answer: B

Explanation:
Many developers want to implement the famous Amazon model that was used to power the “People who bought this also bought these items” feature on Amazon.com. This model is based on a method called Collaborative Filtering. It takes items such as movies, books, and products that were rated highly by a set of users and recommending them to other users who also gave them high ratings. This method works well in domains where explicit ratings or implicit user actions can be gathered and analyzed.

NEW QUESTION 11
Amazon Connect has recently been tolled out across a company as a contact call center The solution has been configured to store voice call recordings on Amazon S3
The content of the voice calls are being analyzed for the incidents being discussed by the call operators Amazon Transcribe is being used to convert the audio to text, and the output is stored on Amazon S3
Which approach will provide the information required for further analysis?

• A. Use Amazon Comprehend with the transcribed files to build the key topics
• B. Use Amazon Translate with the transcribed files to train and build a model for the key topics
• C. Use the AWS Deep Learning AMI with Gluon Semantic Segmentation on the transcribed files to train and build a model for the key topics
• D. Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the transcribed files to generate a word embeddings dictionary for the key topics

Answer: B

NEW QUESTION 12
A Machine Learning Specialist has completed a proof of concept for a company using a small data sample and now the Specialist is ready to implement an end-to-end solution in AWS using Amazon SageMaker The historical training data is stored in Amazon RDS
Which approach should the Specialist use for training a model using that data?

• A. Write a direct connection to the SQL database within the notebook and pull data in
• B. Push the data from Microsoft SQL Server to Amazon S3 using an AWS Data Pipeline and provide the S3 location within the notebook.
• C. Move the data to Amazon DynamoDB and set up a connection to DynamoDB within the notebook to pull data in
• D. Move the data to Amazon ElastiCache using AWS DMS and set up a connection within the notebook to pull data in for fast access.

Answer: B

NEW QUESTION 13
A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.

Based on this information which model would have the HIGHEST accuracy?

• A. Long short-term memory (LSTM) model with scaled exponential linear unit (SELL))
• B. Logistic regression
• C. Support vector machine (SVM) with non-linear kernel
• D. Single perceptron with tanh activation function

Answer: B

NEW QUESTION 14
A Machine Learning Specialist is using an Amazon SageMaker notebook instance in a private subnet of a corporate VPC. The ML Specialist has important data stored on the Amazon SageMaker notebook instance's Amazon EBS volume, and needs to take a snapshot of that EBS volume. However the ML Specialist cannot find the Amazon SageMaker notebook instance's EBS volume or Amazon EC2 instance within the VPC.
Why is the ML Specialist not seeing the instance visible in the VPC?

• A. Amazon SageMaker notebook instances are based on the EC2 instances within the customer account, but they run outside of VPCs.
• B. Amazon SageMaker notebook instances are based on the Amazon ECS service within customer accounts.
• C. Amazon SageMaker notebook instances are based on EC2 instances running within AWS service accounts.
• D. Amazon SageMaker notebook instances are based on AWS ECS instances running within AWS service accounts.

Answer: C

NEW QUESTION 15
A Machine Learning Specialist prepared the following graph displaying the results of k-means for k = [1:10]

Considering the graph, what is a reasonable selection for the optimal choice of k?

• A. 1
• B. 4
• C. 7
• D. 10

Answer: C

NEW QUESTION 16
A Machine Learning Specialist working for an online fashion company wants to build a data ingestion solution for the company's Amazon S3-based data lake.
The Specialist wants to create a set of ingestion mechanisms that will enable future capabilities comprised of:
• Real-time analytics
• Interactive analytics of historical data
• Clickstream analytics
• Product recommendations
Which services should the Specialist use?

• A. AWS Glue as the data dialog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for real-time data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
• B. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for near-realtime data insights; Amazon Kinesis Data Firehose for clickstream analytics; AWS Glue to generate personalized product recommendations
• C. AWS Glue as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for historical data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
• D. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for historical data insights; Amazon DynamoDB streams for clickstream analytics; AWS Glue to generate personalized product recommendations

Answer: A

NEW QUESTION 17
A Machine Learning Specialist is configuring Amazon SageMaker so multiple Data Scientists can access notebooks, train models, and deploy endpoints. To ensure the best operational performance, the Specialist needs to be able to track how often the Scientists are deploying models, GPU and CPU utilization on the deployed SageMaker endpoints, and all errors that are generated when an endpoint is invoked.
Which services are integrated with Amazon SageMaker to track this information? (Select TWO.)

• A. AWS CloudTrail
• B. AWS Health
• C. AWS Trusted Advisor
• D. Amazon CloudWatch
• E. AWS Config

Answer: AD

NEW QUESTION 18
A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.

Based on this information, which model would have the HIGHEST recall with respect to the fraudulent class?

• A. Decision tree
• B. Linear support vector machine (SVM)
• C. Naive Bayesian classifier
• D. Single Perceptron with sigmoidal activation function

Answer: C

NEW QUESTION 19
A Machine Learning Specialist observes several performance problems with the training portion of a machine learning solution on Amazon SageMaker The solution uses a large training dataset 2 TB in size and is using the SageMaker k-means algorithm The observed issues include the unacceptable length of time it takes before the training job launches and poor I/O throughput while training the model
What should the Specialist do to address the performance issues with the current solution?

• A. Use the SageMaker batch transform feature
• B. Compress the training data into Apache Parquet format.
• C. Ensure that the input mode for the training job is set to Pipe.
• D. Copy the training dataset to an Amazon EFS volume mounted on the SageMaker instance.

Answer: B

NEW QUESTION 20
A manufacturer of car engines collects data from cars as they are being driven The data collected includes timestamp, engine temperature, rotations per minute (RPM), and other sensor readings The company wants to predict when an engine is going to have a problem so it can notify drivers in advance to get engine
maintenance The engine data is loaded into a data lake for training
Which is the MOST suitable predictive model that can be deployed into production'?

• A. Add labels over time to indicate which engine faults occur at what time in the future to turn this into a supervised learning problem Use a recurrent neural network (RNN) to train the model to recognize when an engine might need maintenance for a certain fault.
• B. This data requires an unsupervised learning algorithm Use Amazon SageMaker k-means to cluster the data
• C. Add labels over time to indicate which engine faults occur at what time in the future to turn this into a supervised learning problem Use a convolutional neural network (CNN) to train the model to recognize when an engine might need maintenance for a certain fault.
• D. This data is already formulated as a time series Use Amazon SageMaker seq2seq to model the time series.

Answer: B

NEW QUESTION 21
When submitting Amazon SageMaker training jobs using one of the built-in algorithms, which common parameters MUST be specified? (Select THREE.)

• A. The training channel identifying the location of training data on an Amazon S3 bucket.
• B. The validation channel identifying the location of validation data on an Amazon S3 bucket.
• C. The 1AM role that Amazon SageMaker can assume to perform tasks on behalf of the users.
• D. Hyperparameters in a JSON array as documented for the algorithm used.
• E. The Amazon EC2 instance class specifying whether training will be run using CPU or GPU.
• F. The output path specifying where on an Amazon S3 bucket the trained model will persist.

Answer: AEF

NEW QUESTION 22
A company has raw user and transaction data stored in AmazonS3 a MySQL database, and Amazon RedShift A Data Scientist needs to perform an analysis by joining the three datasets from Amazon S3, MySQL, and Amazon RedShift, and then calculating the average-of a few selected columns from the joined data
Which AWS service should the Data Scientist use?

• A. Amazon Athena
• B. Amazon Redshift Spectrum
• C. AWS Glue
• D. Amazon QuickSight

Answer: A

NEW QUESTION 23
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