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MLS-C01復習解答例、MLS-C01科目対策 - Amazon MLS-C01サンプル問題集 - Royalholidayclubbed
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我々は心からあなたが首尾よく試験に合格することを願っています。あなたに便利なオンラインサービスを提供して、Amazon MLS-C01復習解答例試験問題についての全ての質問を解決して差し上げます。RoyalholidayclubbedのAmazonのMLS-C01復習解答例試験問題資料は質が良くて値段が安い製品です。 MLS-C01復習解答例はAmazonのひとつの認証で、MLS-C01復習解答例がAmazonに入るの第一歩として、MLS-C01復習解答例「AWS Certified Machine Learning - Specialty」試験がますます人気があがって、MLS-C01復習解答例に参加するかたもだんだん多くなって、しかしMLS-C01復習解答例認証試験に合格することが非常に難しいで、君はMLS-C01復習解答例に関する試験科目の問題集を購入したいですか？ 優れたキャリアを持ったら、社会と国のために色々な利益を作ることができて、国の経済が継続的に発展していることを進められるようになります。
AWS Certified Specialty MLS-C01 あなたの夢は何ですか。
AWS Certified Specialty MLS-C01復習解答例 - AWS Certified Machine Learning - Specialty Royalholidayclubbedが持つべきなIT問題集を提供するサイトでございます。 あなたは試験の最新バージョンを提供することを要求することもできます。最新のMLS-C01 学習体験談試験問題を知りたい場合、試験に合格したとしてもRoyalholidayclubbedは無料で問題集を更新してあげます。
IT業の多くの人がいくつか認証試験にパスしたくて、それなりの合格証明書が君に最大な上昇空間を与えます。この競争の激しい業界でとんとん拍子に出世させるのはAmazonのMLS-C01復習解答例認定試験ですが、簡単にパスではありません。でもたくさんの方法があって、最も少ない時間をエネルギーをかかるのは最高です。
Amazon MLS-C01復習解答例 - 試験に失敗したら、全額で返金する承諾があります。
全てのIT専門人員はAmazonのMLS-C01復習解答例の認定試験をよく知っていて、その難しい試験に受かることを望んでいます。AmazonのMLS-C01復習解答例の認定試験の認可を取ったら、あなたは望むキャリアを得ることができるようになります。RoyalholidayclubbedのAmazonのMLS-C01復習解答例試験トレーニング資料を利用したら、望むことを取得できます。
我々もオンライン版とソフト版を提供します。すべては豊富な内容があって各自のメリットを持っています。
MLS-C01 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 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: 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
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