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AWS Certified Machine Learning AWS-Certified-Machine-Learning-Specialty 試験に失敗したら、全額で返金する承諾があります。

NewValidDumpsのAmazonのAWS-Certified-Machine-Learning-Specialty - AWS Certified Machine Learning - Specialty復習対策書問題集は総合的にすべてのシラバスと複雑な問題をカバーしています。 あなたは各バーションのAmazonのAWS-Certified-Machine-Learning-Specialty 一発合格試験の資料をダウンロードしてみることができ、あなたに一番ふさわしいバーションを見つけることができます。暇な時間だけでAmazonのAWS-Certified-Machine-Learning-Specialty 一発合格試験に合格したいのですか。

あなたが試験に合格することにヘルプをあげられますから。それにNewValidDumpsは１００パーセント合格率を保証します。あなたが任意の損失がないようにもし試験に合格しなければNewValidDumpsは全額で返金できます。

Amazon AWS-Certified-Machine-Learning-Specialty復習対策書 - あなた自身のために、証明書をもらいます。

競争力が激しい社会に当たり、我々NewValidDumpsは多くの受験生の中で大人気があるのは受験生の立場からAmazon　AWS-Certified-Machine-Learning-Specialty復習対策書試験資料をリリースすることです。たとえば、ベストセラーのAmazon　AWS-Certified-Machine-Learning-Specialty復習対策書問題集は過去のデータを分析して作成ます。ほんとんどお客様は我々NewValidDumpsのAmazon　AWS-Certified-Machine-Learning-Specialty復習対策書問題集を使用してから試験にうまく合格しましたのは弊社の試験資料の有効性と信頼性を説明できます。

現在のIT領域で競争が激しくなっていることは皆は良く知っていますから、みんなはIT認証を通じて自分の価値を高めたいです。私もそう思いますが、IT認証は私にとって大変難しいです。

AWS-Certified-Machine-Learning-Specialty PDF DEMO:

QUESTION NO: 1
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

QUESTION NO: 2
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 dimensionality of dense layer next to the flatten layer should be increased because the model is not complex enough.
C. The epoch number should be increased because the optimization process was terminated before it reached the global minimum.
D. The dropout rate at the flatten layer should be increased because the model is not generalized enough.
Answer: C

QUESTION NO: 3
A Machine Learning Specialist working for an online fashion company wants to build a data ingestion solution for the company's Amazon S3-based data lake.
The Specialist wants to create a set of ingestion mechanisms that will enable future capabilities comprised of:
* Real-time analytics
* Interactive analytics of historical data
* Clickstream analytics
* Product recommendations
Which services should the Specialist use?
A. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data
Analytics for historical data insights; Amazon DynamoDB streams for clickstream analytics; AWS Glue to generate personalized product recommendations
B. AWS Glue as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for historical data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
C. AWS Glue as the data dialog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for real-time data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
D. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data
Analytics for near-realtime data insights; Amazon Kinesis Data Firehose for clickstream analytics; AWS
Glue to generate personalized product recommendations
Answer: C

QUESTION NO: 4
A Machine Learning Specialist has created a deep learning neural network model that performs well on the training data but performs poorly on the test data.
Which of the following methods should the Specialist consider using to correct this? (Select THREE.)
A. Decrease dropout.
B. Increase regularization.
C. Increase feature combinations.
D. Decrease feature combinations.
E. Decrease regularization.
F. Increase dropout.
Answer: A,B,C

QUESTION NO: 5
A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input hyperparameter range(s) Which visualization will accomplish this?
A. A scatter plot with points colored by target variable that uses (-Distributed Stochastic Neighbor
Embedding (I-SNE) to visualize the large number of input variables in an easier-to-read dimension.
B. A scatter plot showing (he performance of the objective metric over each training iteration
C. A histogram showing whether the most important input feature is Gaussian.
D. A scatter plot showing the correlation between maximum tree depth and the objective metric.
Answer: A

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Updated: May 28, 2022