Latest Update Lead4Pass MLS-C01 dumps for 2023

The latest updated Lead4Pass MLS-C01 dumps contain 215 latest exam questions and answers, the best exam material for the 2023 AWS Certified Machine Learning – Specialty certification exam.

Download the latest MLS-C01 dumps: https://www.lead4pass.com/aws-certified-machine-learning-specialty.html, use Lead4Pass to provide PDF and VCE study tools to help you study the complete exam questions efficiently and guarantee 100% success in passing the exam.

Latest Amazon MLS-C01 exam questions and answers

Read some of the latest Amazon MLS-C01 exam questions and answers online:

Number of exam questionsExam nameExam codeLast updated
15AWS Certified Machine Learning – SpecialtyMLS-C01MLS-C01 dumps
Question 1:

A Machine Learning Specialist is building a model to predict future employment rates based on a wide range of economic factors While exploring the data, the Specialist notices that the magnitude of the input features varies greatly The Specialist does not want variables with a larger magnitude to dominate the model

What should the Specialist do to prepare the data for model training\’?

A. Apply quantile binning to group the data into categorical bins to keep any relationships in the data by replacing the magnitude with distribution

B. Apply the Cartesian product transformation to create new combinations of fields that are independent of the magnitude

C. Apply normalization to ensure each field will have a mean of 0 and a variance of 1 to remove any significant magnitude

D. Apply the orthogonal sparse Diagram (OSB) transformation to apply a fixed-size sliding window to generate new features of a similar magnitude.

Correct Answer: C

Reference: https://docs.aws.amazon.com/machine-learning/latest/dg/data-transformations-reference.html

Question 2:

A Mobile Network Operator is building an analytics platform to analyze and optimize a company\’s operations using Amazon Athena and Amazon S3

The source systems send data in CSV format in real time The Data Engineering team wants to transform the data to the Apache Parquet format before storing it on Amazon S3

Which solution takes the LEAST effort to implement?

A. Ingest. CSV data using Apache Kafka Streams on Amazon EC2 instances and use Kafka Connect S3 to serialize data as Parquet

B. Ingest. CSV data from Amazon Kinesis Data Streams and use Amazon Glue to convert data into Parquet.

C. Ingest. CSV data using Apache Spark Structured Streaming in an Amazon EMR cluster and use Apache Spark to convert data into Parquet.

D. Ingest. CSV data from Amazon Kinesis Data Streams and use Amazon Kinesis Data Firehose to convert data into Parquet.

Correct Answer: C

Question 3:

A Data Scientist needs to migrate an existing on-premises ETL process to the cloud. The current process

runs at regular time intervals and uses PySpark to combine and format multiple large data sources into a

single consolidated output for downstream processing.

The Data Scientist has been given the following requirements for the cloud solution:

Combine multiple data sources.

Reuse existing PySpark logic.

Run the solution on the existing schedule.

Minimize the number of servers that will need to be managed.

Which architecture should the Data Scientist use to build this solution?

A. Write the raw data to Amazon S3. Schedule an AWS Lambda function to submit a Spark step to a persistent Amazon EMR cluster based on the existing schedule. Use the existing PySpark logic to run the ETL job on the EMR cluster. Output the results to a “processed” location in Amazon S3 that is accessible for downstream use.

B. Write the raw data to Amazon S3. Create an AWS Glue ETL job to perform the ETL processing against the input data. Write the ETL job in PySpark to leverage the existing logic. Create a new AWS Glue trigger to trigger the ETL job based on the existing schedule. Configure the output target of the ETL job to write to a “processed” location in Amazon S3 that is accessible for downstream use.

C. Write the raw data to Amazon S3. Schedule an AWS Lambda function to run on the existing schedule and process the input data from Amazon S3. Write the Lambda logic in Python and implement the existing PySpark logic to perform the ETL process. Have the Lambda function output the results to a “processed” location in Amazon S3 that is accessible for downstream use.

D. Use Amazon Kinesis Data Analytics to stream the input data and perform real-time SQL queries against the stream to carry out the required transformations within the stream. Deliver the output results to a “processed” location in Amazon S3 that is accessible for downstream use.

Correct Answer: D

Exam B

Question 4:

A Machine Learning Specialist is implementing a full Bayesian network on a dataset that describes public transit in New York City. One of the random variables is discrete and represents the number of minutes New Yorkers wait for a bus given that the buses cycle every 10 minutes, with a mean of 3 minutes.

Which prior probability distribution should the ML Specialist use for this variable?

A. Poisson distribution

B. Uniform distribution

C. Normal distribution

D. Binomial distribution

Correct Answer: D

Question 5:

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?

A. Latent Dirichlet Allocation (LDA)

B. Recurrent neural network (RNN)

C. K-means

D. Convolutional neural network (CNN)

Correct Answer: C

Question 6:

A Machine Learning Specialist is attempting to build a linear regression model.

mls-c01 questions 6

Given the displayed residual plot only, what is the MOST likely problem with the model?

A. Linear regression is inappropriate. The residuals do not have constant variance.

B. Linear regression is inappropriate. The underlying data has outliers.

C. Linear regression is appropriate. The residuals have a zero mean.

D. Linear regression is appropriate. The residuals have constant variance.

Correct Answer: D

Question 7:

A company that manufactures mobile devices wants to determine and calibrate the appropriate sales price for its devices. The company is collecting the relevant data and is determining data features that it can use to train machine learning (ML) models. There are more than 1,000 features, and the company wants to determine the primary features that contribute to the sales price.

Which techniques should the company use for feature selection? (Choose three.)

A. Data scaling with standardization and normalization

B. Correlation plot with heat maps

C. Data binning

D. Univariate selection

E. Feature importance with a tree-based classifier

F. Data augmentation

Correct Answer: CDF

Reference: https://towardsdatascience.com/an-overview-of-data-preprocessing-features-enrichment-automaticfeature-selection-60b0c12d75ad

Question 8:

A web-based company wants to improve its conversion rate on its landing page. Using a large historical dataset of customer visits, the company has repeatedly trained a multi-class deep learning network algorithm on Amazon SageMaker. However, there is an overfitting problem: training data shows 90% accuracy in predictions, while test data shows 70% accuracy only.

The company needs to boost the generalization of its model before deploying it into production to maximize conversions of visits to purchases.

Which action is recommended to provide the HIGHEST accuracy model for the company\’s test and validation data?

A. Increase the randomization of training data in the mini-batches used in training.

B. Allocate a higher proportion of the overall data to the training dataset

C. Apply L1 or L2 regularization and dropouts to the training.

D. Reduce the number of layers and units (or neurons) from the deep learning network.

Correct Answer: D

Question 9:

A Machine Learning Specialist receives customer data for an online shopping website. The data includes demographics, past visits, and locality information. The Specialist must develop a machine learning approach to identify the customer shopping patterns, preferences, and trends to enhance the website for better service and smart recommendations.

Which solution should the Specialist recommend?

A. Latent Dirichlet Allocation (LDA) for the given collection of discrete data to identify patterns in the customer database.

B. A neural network with a minimum of three layers and random initial weights to identify patterns in the customer database

C. Collaborative filtering based on user interactions and correlations to identify patterns in the customer database

D. Random Cut Forest (RCF) over random subsamples to identify patterns in the customer database

Correct Answer: C

Question 10:

A company wants to predict the sale prices of houses based on available historical sales data. The target variable in the company\’s dataset is the sale price. The features include parameters such as the lot size, living area measurements, non-living area measurements, number of bedrooms, number of bathrooms, year built, and postal code. The company wants to use multi-variable linear regression to predict house sale prices.

Which step should a machine learning specialist take to remove features that are irrelevant to the analysis and reduce the model\’s complexity?

A. Plot a histogram of the features and compute their standard deviation. Remove features with high variance.

B. Plot a histogram of the features and compute their standard deviation. Remove features with low variance.

C. Build a heatmap showing the correlation of the dataset against itself. Remove features with low mutual correlation scores.

D. Run a correlation check of all features against the target variable. Remove features with low target variable correlation scores.

Correct Answer: D

Question 11:

A Machine Learning Specialist is deciding between building a naive Bayesian model or a full Bayesian network for a classification problem. The Specialist computes the Pearson correlation coefficients between each feature and finds that their absolute values range between 0.1 to 0.95.

Which model describes the underlying data in this situation?

A. A naive Bayesian model, since the features are all conditionally independent.

B. A full Bayesian network, since the features are all conditionally independent.

C. A naive Bayesian model, since some of the features are statistically dependent.

D. A full Bayesian network, since some of the features are statistically dependent.

Correct Answer: C

Question 12:

A manufacturing company asks its machine learning specialist to develop a model that classifies defective parts into one of eight defect types. The company has provided roughly 100,000 images per defect type for training. During the initial training of the image classification model, the specialist notices that the validation accuracy is 80%, while the training accuracy is 90%. It is known that human-level performance for this type of image classification is around 90%.

What should the specialist consider to fix this issue?

A. A longer training time

B. Making the network larger

C. Using a different optimizer

D. Using some form of regularization

Correct Answer: D

Reference: https://acloud.guru/forums/aws-certified-machine-learning-specialty/discussion/MGdBUKmQ02zC3uOq4VL/AWS%20Exam%20Machine%20Learning

Question 13:

A Machine Learning Specialist has built a model using Amazon SageMaker built-in algorithms and is not getting the 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 14:

A city wants to monitor its air quality to address the consequences of air pollution A Machine Learning Specialist needs to forecast the air quality in parts per million of contaminates for the next 2 days in the city As this is a prototype, only daily data from the last year is available

Which model is MOST likely to provide the best results in Amazon SageMaker?

A. Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the single time series consisting of the full year of data with a predictor_type of the regressor.

B. Use Amazon SageMaker Random Cut Forest (RCF) on the single time series consisting of the full year of data.

C. Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_type of the regressor.

D. Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_type of the classifier.

Correct Answer: C

Reference: https://aws.amazon.com/blogs/machine-learning/build-a-model-to-predict-the-impact-ofweather-on-urban-air-quality-using-amazon-sagemaker/?ref=Welcome.AI

Question 15:

A Data Scientist is developing a binary classifier to predict whether a patient has a particular disease on a series of test results. The Data Scientist has data on 400 patients randomly selected from the population. The disease is seen in 3% of the population.

Which cross-validation strategy should the Data Scientist adopt?

A. A k-fold cross-validation strategy with k=5

B. A stratified k-fold cross-validation strategy with k=5

C. A k-fold cross-validation strategy with k=5 and 3 repeats

D. An 80/20 stratified split between training and validation

Correct Answer: B


Lead4Pass MLS-C01 dumps is the latest AWS Certified Machine Learning – Specialty certification exam material, verified by a team of experts, true and effective. Download
MLS-C01 dumps: https://www.lead4pass.com/aws-certified-machine-learning-specialty.html, Preparing for 2023 helps you pass the exam with ease.