MLS-C01 勉強方法 & Amazon AWS Certified Machine Learning Specialty テスト対策書 - Royalholidayclubbed

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AWS Certified Specialty MLS-C01 近年、IT領域で競争がますます激しくなります。

競争力が激しい社会において、IT仕事をする人は皆、我々RoyalholidayclubbedのMLS-C01 - AWS Certified Machine Learning - Specialty勉強方法を通して自らの幸せを筑く建筑士になれます。 RoyalholidayclubbedのAmazonのMLS-C01 認定テキスト試験トレーニング資料は豊富な知識と経験を持っているIT専門家に研究された成果で、正確度がとても高いです。Royalholidayclubbedに会ったら、最高のトレーニング資料を見つけました。

デーモ版によって、このMLS-C01勉強方法問題集はあなたに適合するかと判断します。適合すると、あなたは安心で購買できます。弊社RoyalholidayclubbedのMLS-C01勉強方法問題集は必ずあなたの成功へ道の秘訣です。

Amazon MLS-C01勉強方法 - もし弊社の問題集を勉強してそれは簡単になります。

時間とお金の集まりより正しい方法がもっと大切です。AmazonのMLS-C01勉強方法試験のために勉強していますなら、Royalholidayclubbedの提供するAmazonのMLS-C01勉強方法試験ソフトはあなたの選びの最高です。我々の目的はあなたにAmazonのMLS-C01勉強方法試験に合格することだけです。試験に失敗したら、弊社は全額で返金します。我々の誠意を信じてください。あなたが順調に試験に合格するように。

弊社の資料を使って、１００％に合格を保証いたします。RoyalholidayclubbedはIT試験問題集を提供するウエブダイトで、ここによく分かります。

MLS-C01 PDF DEMO:

QUESTION NO: 1
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: 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 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: 4
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

QUESTION NO: 5
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

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Updated: May 28, 2022

by RHC.

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