ほかの人はあなたの成績に驚いているとき、ひょっとしたら、あなたはよりよい仕事を探しましたかもしれません。地下鉄でほかの人はぽかんと座っているとき、あなたはPadまたはスマホでPDF版のAmazonのAWS-Certified-Machine-Learning-Specialty予想試験試験の資料を読むことができます。ほかの人がインタネットでゲームを遊んでいるとき、あなたはオンラインでAmazonのAWS-Certified-Machine-Learning-Specialty予想試験の問題集をすることができます。 信じられなら利用してみてください。不合格になればGoldmile-Infobizは全額返金のことができますから、絶対損にならないです。 AmazonのAWS-Certified-Machine-Learning-Specialty予想試験問題集は専業化のチームが改革とともに、開発される最新版のことです。
つまりAWS-Certified-Machine-Learning-Specialty予想試験練習問題はあなたの最も正しい選択です。
AWS Certified Machine Learning AWS-Certified-Machine-Learning-Specialty予想試験 - AWS Certified Machine Learning - Specialty 我々の商品はあなたの認可を得られると希望します。 AWS-Certified-Machine-Learning-Specialty 問題集復習教材は有効的な資料です。AWS-Certified-Machine-Learning-Specialty 問題集試験は難しいです。
Goldmile-Infobizの提供するAmazonのAWS-Certified-Machine-Learning-Specialty予想試験試験の資料とソフトは経験が豊富なITエリートに開発されて、何回も更新されています。何十ユーロだけでこのような頼もしいAmazonのAWS-Certified-Machine-Learning-Specialty予想試験試験の資料を得ることができます。試験に合格してからあなたがよりよい仕事と給料がもらえるかもしれません。
また、Amazon AWS-Certified-Machine-Learning-Specialty予想試験問題集は的中率が高いです。
Goldmile-Infobizの専門家チームがAmazonのAWS-Certified-Machine-Learning-Specialty予想試験認証試験に対して最新の短期有効なトレーニングプログラムを研究しました。AmazonのAWS-Certified-Machine-Learning-Specialty予想試験「AWS Certified Machine Learning - Specialty」認証試験に参加者に対して30時間ぐらいの短期の育成訓練でらくらくに勉強しているうちに多くの知識を身につけられます。
弊社の専門家は経験が豊富で、研究した問題集がもっとも真題と近づいて現場試験のうろたえることを避けます。Amazon AWS-Certified-Machine-Learning-Specialty予想試験認証試験を通るために、いいツールが必要です。
AWS-Certified-Machine-Learning-Specialty PDF DEMO:
QUESTION NO: 1
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: 2
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: 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