Month End Sale Limited Time 65% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: get65

Amazon Web Services Updated MLS-C01 Exam Questions and Answers by inara

Page: 11 / 23

Amazon Web Services MLS-C01 Exam Overview :

Exam Name: AWS Certified Machine Learning - Specialty
Exam Code: MLS-C01 Dumps
Vendor: Amazon Web Services Certification: AWS Certified Specialty
Questions: 322 Q&A's Shared By: inara
Question 44

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?

Options:

A.

Receiver operating characteristic (ROC) curve

B.

Misclassification rate

C.

Root Mean Square Error (RM&)

D.

L1 norm

Discussion
Question 45

A bank has collected customer data for 10 years in CSV format. The bank stores the data in an on-premises server. A data science team wants to use Amazon SageMaker to build and train a machine learning (ML) model to predict churn probability. The team will use the historical data. The data scientists want to perform data transformations quickly and to generate data insights before the team builds a model for production.

Which solution will meet these requirements with the LEAST development effort?

Options:

A.

Upload the data into the SageMaker Data Wrangler console directly. Perform data transformations and generate insights within Data Wrangler.

B.

Upload the data into an Amazon S3 bucket. Allow SageMaker to access the data that is in the bucket. Import the data from the S3 bucket into SageMaker Data Wrangler. Perform data transformations and generate insights within Data Wrangler.

C.

Upload the data into the SageMaker Data Wrangler console directly. Allow SageMaker and Amazon QuickSight to access the data that is in an Amazon S3 bucket. Perform data transformations in Data Wrangler and save the transformed data into a second S3 bucket. Use QuickSight to generate data insights.

D.

Upload the data into an Amazon S3 bucket. Allow SageMaker to access the data that is in the bucket. Import the data from the bucket into SageMaker Data Wrangler. Perform data transformations in Data Wrangler. Save the data into a second S3 bucket. Use a SageMaker Studio notebook to generate data insights.

Discussion
Question 46

A company is building a demand forecasting model based on machine learning (ML). In the development stage, an ML specialist uses an Amazon SageMaker notebook to perform feature engineering during work hours that consumes low amounts of CPU and memory resources. A data engineer uses the same notebook to perform data preprocessing once a day on average that requires very high memory and completes in only 2 hours. The data preprocessing is not configured to use GPU. All the processes are running well on an ml.m5.4xlarge notebook instance.

The company receives an AWS Budgets alert that the billing for this month exceeds the allocated budget.

Which solution will result in the MOST cost savings?

Options:

A.

Change the notebook instance type to a memory optimized instance with the same vCPU number as the ml.m5.4xlarge instance has. Stop the notebook when it is not in use. Run both data preprocessing and feature engineering development on that instance.

B.

Keep the notebook instance type and size the same. Stop the notebook when it is not in use. Run data preprocessing on a P3 instance type with the same memory as the ml.m5.4xlarge instance by using Amazon SageMaker Processing.

C.

Change the notebook instance type to a smaller general-purpose instance. Stop the notebook when it is not in use. Run data preprocessing on an ml. r5 instance with the same memory size as the ml.m5.4xlarge instance by using Amazon SageMaker Processing.

D.

Change the notebook instance type to a smaller general-purpose instance. Stop the notebook when it is not in use. Run data preprocessing on an R5 instance with the same memory size as the ml.m5.4xlarge instance by using the Reserved Instance option.

Discussion
Question 47

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)

Discussion
Yusra
I passed my exam. Cramkey Dumps provides detailed explanations for each question and answer, so you can understand the concepts better.
Alisha Aug 29, 2024
I recently used their dumps for the certification exam I took and I have to say, I was really impressed.
Nia
Why are these Dumps so important for students these days?
Mary Oct 9, 2024
With the constantly changing technology and advancements in the industry, it's important for students to have access to accurate and valid study material. Cramkey Dumps provide just that. They are constantly updated to reflect the latest changes and ensure that the information is up-to-date.
Ace
No problem! I highly recommend Cramkey Dumps to anyone looking to pass their certification exams. They will help you feel confident and prepared on exam day. Good luck!
Harris Oct 31, 2024
That sounds amazing. I'll definitely check them out. Thanks for the recommendation!
Sarah
Yeah, I was so relieved when I saw that the question appeared in the exam were similar to their exam dumps. It made the exam a lot easier and I felt confident going into it.
Aaliyah Aug 27, 2024
Same here. I've heard mixed reviews about using exam dumps, but for us, it definitely paid off.
Page: 11 / 23
Title
Questions
Posted

MLS-C01
PDF

$36.75  $104.99

MLS-C01 Testing Engine

$43.75  $124.99

MLS-C01 PDF + Testing Engine

$57.75  $164.99