최신MLA-C01최고품질인증시험덤프데모인증덤프샘플문제체험하기

Pass4Tes가 제공하는 제품을 사용함으로 여러분은 IT업계하이클래스와 멀지 않았습니다. Pass4Tes 가 제공하는 인증시험덤프는 여러분을Amazon인증MLA-C01시험을 안전하게 통과는 물론 관연전업지식장악에도 많은 도움이 되며 또한 우리는 일년무료 업뎃서비스를 제공합니다.

우선 우리Itexamdump 사이트에서Amazon MLA-C01관련자료의 일부 문제와 답 등 샘플을 제공함으로 여러분은 무료로 다운받아 체험해보실 수 있습니다.체험 후 우리의Itexamdump에 신뢰감을 느끼게 됩니다. Itexamdump에서 제공하는Amazon MLA-C01덤프로 시험 준비하시면 편안하게 시험을 패스하실 수 있습니다.

>> MLA-C01최고품질 인증시험덤프데모 <<

최신 AWS Certified Associate MLA-C01 무료샘플문제 (Q64-Q69):

질문 # 64
A credit card company has a fraud detection model in production on an Amazon SageMaker endpoint. The company develops a new version of the model. The company needs to assess the new model's performance by using live data and without affecting production end users.
Which solution will meet these requirements?

A. Set up blue/green deployments with all-at-once traffic shifting.
B. Set up shadow testing with a shadow variant of the new model.
C. Set up SageMaker Debugger and create a custom rule.
D. Set up blue/green deployments with canary traffic shifting.

정답：B

설명：
Shadow testing allows you to send a copy of live production traffic to a shadow variant of the new model while keeping the existing production model unaffected. This enables you to evaluate the performance of the new model in real-time with live data without impacting end users. SageMaker endpoints support this setup by allowing traffic mirroring to the shadow variant, making it an ideal solution for assessing the new model's performance.

질문 # 65
A company has an ML model that needs to run one time each night to predict stock values. The model input is
3 MB of data that is collected during the current day. The model produces the predictions for the next day.
The prediction process takes less than 1 minute to finish running.
How should the company deploy the model on Amazon SageMaker to meet these requirements?

A. Use a serverless inference endpoint. Set the MaxConcurrency parameter to 1.
B. Use a real-time endpoint. Configure an auto scaling policy to scale the model to 0 when the model is not in use.
C. Use a multi-model serverless endpoint. Enable caching.
D. Use an asynchronous inference endpoint. Set the InitialInstanceCount parameter to 0.

정답：A

설명：
A serverless inference endpoint in Amazon SageMaker is ideal for use cases where the model is invoked infrequently, such as running one time each night. It eliminates the cost of idle resources when the model is not in use. Setting the MaxConcurrency parameter to 1 ensures cost-efficiency while supporting the required single nightly invocation. This solution minimizes costs and matches the requirement to process a small amount of data quickly.

질문 # 66
An ML engineer needs to use Amazon SageMaker Feature Store to create and manage features to train a model.
Select and order the steps from the following list to create and use the features in Feature Store. Each step should be selected one time. (Select and order three.)
* Access the store to build datasets for training.
* Create a feature group.
* Ingest the records.

정답：

설명：

Explanation:

Step 1: Create a feature group.Step 2: Ingest the records.Step 3: Access the store to build datasets for training.
* Step 1: Create a Feature Group
* Why?A feature group is the foundational unit in SageMaker Feature Store, where features are defined, stored, and organized. Creating a feature group specifies the schema (name, data type) for the features and the primary keys for data identification.
* How?Use the SageMaker Python SDK or AWS CLI to define the feature group by specifying its name, schema, and S3 storage location for offline access.
* Step 2: Ingest the Records
* Why?After creating the feature group, the raw data must be ingested into the Feature Store. This step populates the feature group with data, making it available for both real-time and offline use.
* How?Use the SageMaker SDK or AWS CLI to batch-ingest historical data or stream new records into the feature group. Ensure the records conform to the feature group schema.
* Step 3: Access the Store to Build Datasets for Training
* Why?Once the features are stored, they can be accessed to create training datasets. These datasets combine relevant features into a single format for machine learning model training.
* How?Use the SageMaker Python SDK to query the offline store or retrieve real-time features using the online store API. The offline store is typically used for batch training, while the online store is used for inference.
Order Summary:
* Create a feature group.
* Ingest the records.
* Access the store to build datasets for training.
This process ensures the features are properly managed, ingested, and accessible for model training using Amazon SageMaker Feature Store.

질문 # 67
A company has historical data that shows whether customers needed long-term support from company staff.
The company needs to develop an ML model to predict whether new customers will require long-term support.
Which modeling approach should the company use to meet this requirement?

A. Linear regression
B. Logistic regression
C. Anomaly detection
D. Semantic segmentation

정답：B

설명：
Logistic regression is a suitable modeling approach for this requirement because it is designed for binary classification problems, such as predicting whether a customer will require long-term support ("yes" or "no").
It calculates the probability of a particular class and is widely used for tasks like this where the outcome is categorical.

질문 # 68
An ML engineer needs to use an ML model to predict the price of apartments in a specific location.
Which metric should the ML engineer use to evaluate the model's performance?

A. Area Under the ROC Curve (AUC)
B. Accuracy
C. Mean absolute error (MAE)
D. F1 score

정답：C

설명：
When predicting continuous variables, such as apartment prices, it's essential to evaluate the model's performance using appropriate regression metrics. The Mean Absolute Error (MAE) is a widely used metric for this purpose.
Understanding Mean Absolute Error (MAE):
MAE measures the average magnitude of errors in a set of predictions, without considering their direction. It calculates the average absolute difference between predicted values and actual values, providing a straightforward interpretation of prediction accuracy.
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Advantages of MAE:
* Interpretability:MAE is expressed in the same units as the target variable, making it easy to understand.
* Robustness to Outliers:Unlike metrics that square the errors (e.g., Mean Squared Error), MAE does not disproportionately penalize larger errors, making it more robust to outliers.
Comparison with Other Metrics:
* Accuracy, AUC, F1 Score:These metrics are designed for classification tasks, where the goal is to predict discrete labels. They are not suitable for regression problems involving continuous target variables.
* Mean Squared Error (MSE):While MSE also measures prediction errors, it squares the differences, giving more weight to larger errors. This can be useful in certain contexts but may be sensitive to outliers.
Conclusion:
For evaluating the performance of a model predicting apartment prices-a continuous variable-MAE is an appropriate and effective metric. It provides a clear indication of the average prediction error in the same units as the target variable, facilitating straightforward interpretation and comparison.
References:
* Regression Metrics - GeeksforGeeks
* Evaluation Metrics for Your Regression Model - Analytics Vidhya
* Regression Metrics for Machine Learning - Machine Learning Mastery

질문 # 69
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Itexamdump의 도움으로 여러분은 많은 시간과 돈을 들이지 않으셔도 혹은 여러학원등을 다니시지 않으셔도 우리 덤프로 안전하게 시험을 통과하실 수 있습니다.Amazon MLA-C01시험자료는 우리 Itexamdump에서 실제시험에 의하여 만들어진 것입니다. 지금까지의 시험문제와 답과 시험문제분석 등입니다. Itexamdump에서 제공하는Amazon MLA-C01시험자료의 문제와 답은 실제시험의 문제와 답과 아주 비슷합니다.

MLA-C01시험대비 덤프데모: https://www.itexamdump.com/MLA-C01.html

Amazon MLA-C01최고품질 인증시험덤프데모 시험합격하면 좋은 소식 전해주세요, Amazon MLA-C01최고품질 인증시험덤프데모 Pass4Tes시험문제와 답이야 말로 퍼펙트한 자료이죠, Itexamdump의Amazon인증 MLA-C01덤프는 실제시험 출제방향에 초점을 두어 연구제작한 시험준비공부자료로서 높은 시험적중율과 시험패스율을 자랑합니다.국제적으로 승인해주는 IT자격증을 취득하시면 취직 혹은 승진이 쉬워집니다, Itexamdump는 당신을 위해Amazon MLA-C01덤프로Amazon MLA-C01인증시험이라는 높은 벽을 순식간에 무너뜨립니다, 이러한 사이트에서 학습가이드와 온라인서비스도 지원되고 있습니다만 Itexamdump MLA-C01시험대비 덤프데모 는 이미 이러한 사이트를 뛰어넘은 실력으로 업계에서 우리만의 이미지를 지키고 있습니다.

침대에 앉아 멍하니 한숨을 내쉬던 장 여사는 무언가 생각이 난 듯, 자리에서 일어나MLA-C01갑자기 외출 준비를 시작했다, 괜히 힘든 시간만 더 길어진 것 같기도 했다, 시험합격하면 좋은 소식 전해주세요, Pass4Tes시험문제와 답이야 말로 퍼펙트한 자료이죠.

MLA-C01최고품질 인증시험덤프데모 시험 최신버전 덤프자료 다운

Itexamdump의Amazon인증 MLA-C01덤프는 실제시험 출제방향에 초점을 두어 연구제작한 시험준비공부자료로서 높은 시험적중율과 시험패스율을 자랑합니다.국제적으로 승인해주는 IT자격증을 취득하시면 취직 혹은 승진이 쉬워집니다.

Itexamdump는 당신을 위해Amazon MLA-C01덤프로Amazon MLA-C01인증시험이라는 높은 벽을 순식간에 무너뜨립니다, 이러한 사이트에서 학습가이드와 온라인서비스도 지원되고 있습니다만 Itexamdump 는 이미 이러한 사이트를 뛰어넘은 실력으로 업계에서 우리만의 이미지를 지키고 있습니다.

Carl Walsh Carl Walsh

Biography

최신MLA-C01최고품질인증시험덤프데모인증덤프샘플문제체험하기

최신 업데이트버전 MLA-C01최고품질 인증시험덤프데모 덤프공부자료

최신 AWS Certified Associate MLA-C01 무료샘플문제 (Q64-Q69):

MLA-C01최고품질 인증시험덤프데모 시험 최신버전 덤프자료 다운