どんな業界で自分に良い昇進機会があると希望する職人がとても多いと思って、IT業界にも例外ではありません。ITの専門者はAmazonのMLS-C01ミシュレーション問題認定試験があなたの願望を助けって実現できるのがよく分かります。Omgzlookはあなたの夢に実現させるサイトでございます。 OmgzlookのAmazonのMLS-C01ミシュレーション問題認定試験に準備するために色々な方法がありますが、Omgzlookは初めて試験を受けるあなたが一回で試験に合格して、認証資格を取ることを保証します。 Omgzlookの専門家チームが君の需要を満たすために自分の経験と知識を利用してAmazonのMLS-C01ミシュレーション問題認定試験対策模擬テスト問題集が研究しました。
AWS Certified Specialty MLS-C01 あなたは最高のトレーニング資料を手に入れました。
現在、AmazonのMLS-C01 - AWS Certified Machine Learning - Specialtyミシュレーション問題認定試験に受かりたいIT専門人員がたくさんいます。 ITが好きですか。ITを通して自分の実力を証明したいのですか。
Omgzlookは優れたIT情報のソースを提供するサイトです。Omgzlookで、あなたの試験のためのテクニックと勉強資料を見つけることができます。OmgzlookのAmazonのMLS-C01ミシュレーション問題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。
Amazon MLS-C01ミシュレーション問題 - Omgzlookは君にとってベストな選択になります。
あなたは君の初めてのAmazonのMLS-C01ミシュレーション問題認定試験を受ける時に認定試験に合格したいか。Omgzlookでは、私たちは君のすべての夢を叶えさせて、君の最も早い時間でAmazonのMLS-C01ミシュレーション問題認定試験に合格するということを保証します。OmgzlookのAmazonのMLS-C01ミシュレーション問題試験トレーニング資料は豊富な経験を持っているIT専門家が研究したもので、問題と解答が緊密に結んでいるものです。Omgzlookを選ぶなら、絶対に後悔させません。
OmgzlookのAmazonのMLS-C01ミシュレーション問題試験トレーニング資料は試験問題と解答を含まれて、豊富な経験を持っているIT業種の専門家が長年の研究を通じて作成したものです。その権威性は言うまでもありません。
MLS-C01 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