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MLS-C01

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QUESTION 1 #

A Machine Learning Specialist is developing a custom video recommendation model for an application. The dataset used to train this model is very large with millions of data points and is hosted in an Amazon S3 bucket. 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.

Which approach allows the Specialist to use all the data to train the model?

A. Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.

B. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to the instance. Train on a small amount of the data to verify the training code and hyperparameters. Go back to Amazon SageMaker and train using the full dataset

C. 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. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.

D. Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to train the full dataset.

Correct Answer: A

QUESTION 2 #

This graph shows the training and validation loss against the epochs for a neural network.
The network being trained is as follows:
1. Two dense layers, one output neuron
2. 100 neurons in each layer
3. 100 epochs
4. Random initialization of weights

Which technique can be used to improve model performance in terms of accuracy in the validation set?

A. Early stopping
B. Random initialization of weights with appropriate seed
C. Increasing the number of epochs
D. Adding another layer with the 100 neurons
Correct Answer: C

QUESTION 3 #

An online reseller has a large, multi-column dataset with one column missing 30% of its data A Machine Learning Does the specialist believe that certain columns in the dataset could be used to reconstruct the missing data.

Which reconstruction approach should the Specialist use to preserve the integrity of the dataset?

A. Listwise deletion
B. Last observation carried forward
C. Multiple imputation
D. Mean substitution
Correct Answer: C
Reference: https://worldwidescience.org/topicpages/i/imputing+missing+values.html

QUESTION 4 #

A company uses a long short-term memory (LSTM) model to evaluate the risk factors of a particular energy sector.

The model reviews multi-page text documents to analyze each sentence of the text and categorize it as either a potential risk or no risk. The model is not performing well, even though the Data Scientist has experimented with many different network structures and tuned the corresponding hyperparameters.

Which approach will provide the MAXIMUM performance boost?

A. Initialize the words by term frequency-inverse document frequency (TF-IDF) vectors pretrained on a large collection
of news articles related to the energy sector.
B. Use gated recurrent units (GRUs) instead of LSTM and run the training process until the valid ation loss stops
decreasing.
C. Reduce the learning rate and run the training process until the training loss stops decreasing.
D. Initialize the words by word2vec embeddings pretrained on a large collection of news articles related to the energy
sector.
Correct Answer: C

QUESTION 5 #

Machine Learning Specialist is working with a media company to perform classification on popular articles from the company\\’s website. The company is using random forests to classify how popular an article will be before it is published. A sample of the data being used is below.

Given the dataset, the Specialist wants to convert the Day_Of_Week column to binary values.

What technique should be used to convert this column to binary values?

A. Binarization
B. One-hot encoding
C. Tokenization
D. Normalization transformation
Correct Answer: B

QUESTION 6 #

An e-commerce company wants to launch a new cloud-based product recommendation feature for its web application.

Due to data localization regulations, any sensitive data must not leave its on-premises data center, and the product recommendation model must be trained and tested using nonsensitive data only. Data transfer to the cloud must use IPsec.

The web application is hosted on-premises with a PostgreSQL database that contains all the data. The company wants the data to be uploaded securely to Amazon S3 each day for model retraining.

How should a machine learning specialist meet these requirements?

A. Create an AWS Glue job to connect to the PostgreSQL DB instance. Ingest tables without sensitive data through an AWS Site-to-Site VPN connection directly into Amazon S3.
B. Create an AWS Glue job to connect to the PostgreSQL DB instance. Ingest all data through an AWS Site-to-Site VPN connection into Amazon S3 while removing sensitive data using a PySpark job.
C. Use AWS Database Migration Service (AWS DMS) with table mapping to select PostgreSQL tables with no sensitive data through an SSL connection. Replicate data directly into Amazon S3.
D. Use PostgreSQL logical replication to replicate all data to PostgreSQL in Amazon EC2 through AWS Direct Connect with a VPN connection. Use AWS Glue to move data from Amazon EC2 to Amazon S3.
Correct Answer: C
Reference: https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Source.PostgreSQL.html

QUESTION 7 #

A media company with a very large archive of unlabeled images, text, audio, and video footage wishes to index its assets to allow rapid identification of relevant content by the Research team. The company wants to use machine learning to accelerate the efforts of its in-house researchers who have limited machine learning expertise.

Which is the FASTEST route to index the assets?

A. Use Amazon Rekognition, Amazon Comprehend, and Amazon Transcribe to tag data into distinct
categories/classes.
B. Create a set of Amazon Mechanical Turk Human Intelligence Tasks to label all footage.
C. Use Amazon Transcribe to convert speech to text. Use the Amazon SageMaker Neural Topic Model (NTM) and Object Detection algorithms to tag data into distinct categories/classes.
D. Use the AWS Deep Learning AMI and Amazon EC2 GPU instances to create custom models for audio transcription and topic modeling and use object detection to tag data into distinct categories/classes.
Correct Answer: A

QUESTION 8 #

A company is using Amazon Textract to extract textual data from thousands of scanned text-heavy legal documents daily. The company uses this information to process loan applications automatically.

Some of the documents fail business validation and are returned to human reviewers, who investigate the errors. This activity increases the time to process the loan applications.

What should the company do to reduce the processing time of loan applications?

A. Configure Amazon Textract to route low-confidence predictions to Amazon SageMaker Ground Truth. Perform a manual review on those words before performing a business validation.
B. Use an Amazon Textract synchronous operation instead of an asynchronous operation.
C. Configure Amazon Textract to route low-confidence predictions to Amazon Augmented AI (Amazon A2I). Perform a manual review on those words before performing a business validation.
D. Use Amazon Rekognition\’s feature to detect text in an image to extract the data from scanned images. Use this information to process the loan applications.
Correct Answer: C

QUESTION 9 #

A Machine Learning Specialist has built a model using Amazon SageMaker built-in algorithms and is not getting expected accurate results The Specialist wants to use hyperparameter optimization to increase the model\\’s accuracy

Which method is the MOST repeatable and requires the LEAST amount of effort to achieve this?

A. Launch multiple training jobs in parallel with different hyperparameters
B. Create an AWS Step Functions workflow that monitors the accuracy in Amazon CloudWatch Logs and relaunches the training job with a defined list of hyperparameters
C. Create a hyperparameter tuning job and set the accuracy as an objective metric.
D. Create a random walk in the parameter space to iterate through a range of values that should be used for each individual hyperparameter
Correct Answer: B

QUESTION 10 #

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.
Correct Answer: B

QUESTION 11 #

A Data Scientist needs to analyze employment data. The dataset contains approximately 10 million observations on people across 10 different features. During the preliminary analysis, the Data Scientist notices that income and age distributions are not normal. While income levels show a right skew as expected, with fewer individuals having a higher income, the age distribution also shows a right skew, with fewer older individuals participating in the workforce.

Which feature transformations can the Data Scientist apply to fix the incorrectly skewed data? (Choose two.)

A. Cross-validation
B. Numerical value binning
C. high-degree polynomial transformation
D. Logarithmic transformation
E. One hot encoding
Correct Answer: AB

QUESTION 12 #

For the given confusion matrix, what is the recall and precision of the model?

A. Recall = 0.92 Precision = 0.84
B. Recall = 0.84 Precision = 0.8
C. Recall = 0.92 Precision = 0.8
D. Recall = 0.8 Precision = 0.92
Correct Answer: A

QUESTION 13 #

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 data. 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.)

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.
Correct Answer: BDF

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