A Review Of Accurate MLS-C01 Free Exam

NEW QUESTION 1
A Machine Learning Specialist built an image classification deep learning model. However the Specialist ran into an overfitting problem in which the training and testing accuracies were 99% and 75%r respectively.
How should the Specialist address this issue and what is the reason behind it?

• A. The learning rate should be increased because the optimization process was trapped at a local minimum.
• B. The dropout rate at the flatten layer should be increased because the model is not generalized enough.
• C. The dimensionality of dense layer next to the flatten layer should be increased because the model is not complex enough.
• D. The epoch number should be increased because the optimization process was terminated before it reached the global minimum.

Answer: D

NEW QUESTION 2
A 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

Answer: B

NEW QUESTION 3
The displayed graph is from a foresting model for testing a time series.

Considering the graph only, which conclusion should a Machine Learning Specialist make about the behavior of the model?

• A. The model predicts both the trend and the seasonality well.
• B. The model predicts the trend well, but not the seasonality.
• C. The model predicts the seasonality well, but not the trend.
• D. The model does not predict the trend or the seasonality well.

Answer: D

NEW QUESTION 4
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 5
A Data Scientist is developing a machine learning model to predict future patient outcomes based on information collected about each patient and their treatment plans. The model should output a continuous value as its prediction. The data available includes labeled outcomes for a set of 4,000 patients. The study was conducted on a group of individuals over the age of 65 who have a particular disease that is known to worsen with age.
Initial models have performed poorly. While reviewing the underlying data, the Data Scientist notices that, out of 4,000 patient observations, there are 450 where the patient age has been input as 0. The other features for these observations appear normal compared to the rest of the sample population.
How should the Data Scientist correct this issue?

• A. Drop all records from the dataset where age has been set to 0.
• B. Replace the age field value for records with a value of 0 with the mean or median value from the dataset.
• C. Drop the age feature from the dataset and train the model using the rest of the features.
• D. Use k-means clustering to handle missing features.

Answer: A

NEW QUESTION 6
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 7
A Machine Learning Specialist works for a credit card processing company and needs to predict which transactions may be fraudulent in near-real time. Specifically, the Specialist must train a model that returns the probability that a given transaction may be fraudulent
How should the Specialist frame this business problem'?

• A. Streaming classification
• B. Binary classification
• C. Multi-category classification
• D. Regression classification

Answer: A

NEW QUESTION 8
A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket. A Machine Learning Specialist wants to use SQL to run queries on this data.
Which solution requires the LEAST effort to be able to query this data?

• A. Use AWS Data Pipeline to transform the data and Amazon RDS to run queries.
• B. Use AWS Glue to catalogue the data and Amazon Athena to run queries.
• C. Use AWS Batch to run ETL on the data and Amazon Aurora to run the queries.
• D. Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries.

Answer: B

NEW QUESTION 9
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 10
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 11
A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket A Machine Learning Specialist wants to use SQL to run queries on this data. Which solution requires the LEAST effort to be able to query this data?

• A. Use AWS Data Pipeline to transform the data and Amazon RDS to run queries.
• B. Use AWS Glue to catalogue the data and Amazon Athena to run queries
• C. Use AWS Batch to run ETL on the data and Amazon Aurora to run the quenes
• D. Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries

Answer: D

NEW QUESTION 12
Given the following confusion matrix for a movie classification model, what is the true class frequency for Romance and the predicted class frequency for Adventure?

• A. The true class frequency for Romance is 77.56% and the predicted class frequency for Adventure is 20 85%
• B. The true class frequency for Romance is 57.92% and the predicted class frequency for Adventure is 1312%
• C. The true class frequency for Romance is 0 78 and the predicted class frequency for Adventure is (0 47 - 0.32).
• D. The true class frequency for Romance is 77.56% * 0.78 and the predicted class frequency for Adventure is 20 85% ' 0.32

Answer: A

NEW QUESTION 13
An Amazon SageMaker notebook instance is launched into Amazon VPC The SageMaker notebook references data contained in an Amazon S3 bucket in another account The bucket is encrypted using SSE-KMS The instance returns an access denied error when trying to access data in Amazon S3.
Which of the following are required to access the bucket and avoid the access denied error? (Select THREE )

• A. An AWS KMS key policy that allows access to the customer master key (CMK)
• B. A SageMaker notebook security group that allows access to Amazon S3
• C. An 1AM role that allows access to the specific S3 bucket
• D. A permissive S3 bucket policy
• E. An S3 bucket owner that matches the notebook owner
• F. A SegaMaker notebook subnet ACL that allow traffic to Amazon S3.

Answer: ACF

NEW QUESTION 14
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

Answer: B

NEW QUESTION 15
A company's Machine Learning Specialist needs to improve the training speed of a time-series forecasting model using TensorFlow. The training is currently implemented on a single-GPU machine and takes approximately 23 hours to complete. The training needs to be run daily.
The model accuracy js acceptable, but the company anticipates a continuous increase in the size of the training data and a need to update the model on an hourly, rather than a daily, basis. The company also wants to minimize coding effort and infrastructure changes
What should the Machine Learning Specialist do to the training solution to allow it to scale for future demand?

• A. Do not change the TensorFlow cod
• B. Change the machine to one with a more powerful GPU to speed up the training.
• C. Change the TensorFlow code to implement a Horovod distributed framework supported by Amazon SageMake
• D. Parallelize the training to as many machines as needed to achieve the business goals.
• E. Switch to using a built-in AWS SageMaker DeepAR mode
• F. Parallelize the training to as many machines as needed to achieve the business goals.
• G. Move the training to Amazon EMR and distribute the workload to as many machines as needed to achieve the business goals.

Answer: B

NEW QUESTION 16
A Machine Learning Specialist is building a supervised model that will evaluate customers' satisfaction with their mobile phone service based on recent usage The model's output should infer whether or not a customer is likely to switch to a competitor in the next 30 days
Which of the following modeling techniques should the Specialist use1?

• A. Time-series prediction
• B. Anomaly detection
• C. Binary classification
• D. Regression

Answer: D

NEW QUESTION 17
A manufacturing company has a large set of labeled historical sales data The manufacturer would like to predict how many units of a particular part should be produced each quarter Which machine learning approach should be used to solve this problem?

• A. Logistic regression
• B. Random Cut Forest (RCF)
• C. Principal component analysis (PCA)
• D. Linear regression

Answer: B

NEW QUESTION 18
A Machine Learning Specialist is developing recommendation engine for a photography blog Given a picture, the recommendation engine should show a picture that captures similar objects The Specialist would like to create a numerical representation feature to perform nearest-neighbor searches
What actions would allow the Specialist to get relevant numerical representations?

• A. Reduce image resolution and use reduced resolution pixel values as features
• B. Use Amazon Mechanical Turk to label image content and create a one-hot representation indicating the presence of specific labels
• C. Run images through a neural network pie-trained on ImageNet, and collect the feature vectors from the penultimate layer
• D. Average colors by channel to obtain three-dimensional representations of images.

Answer: A

NEW QUESTION 19
An online reseller has a large, multi-column dataset with one column missing 30% of its data A Machine Learning Specialist believes 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

Answer: C

NEW QUESTION 20
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 21
A monitoring service generates 1 TB of scale metrics record data every minute A Research team performs queries on this data using Amazon Athena The queries run slowly due to the large volume of data, and the team requires better performance
How should the records be stored in Amazon S3 to improve query performance?

• A. CSV files
• B. Parquet files
• C. Compressed JSON
• D. RecordIO

Answer: B

NEW QUESTION 22
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 23
A Machine Learning Specialist trained a regression model, but the first iteration needs optimizing. The Specialist needs to understand whether the model is more frequently overestimating or underestimating the
target.
What option can the Specialist use to determine whether it is overestimating or underestimating the target value?

• A. Root Mean Square Error (RMSE)
• B. Residual plots
• C. Area under the curve
• D. Confusion matrix

Answer: C

NEW QUESTION 24
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