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AWS Certified Specialty MLS-C01 きっと望んでいるでしょう。
AWS Certified Specialty MLS-C01試験概要 - AWS Certified Machine Learning - Specialty Omgzlookの商品はとても頼もしい試験の練習問題と解答は非常に正確でございます。 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 対応受験試験問題を知りたい場合、試験に合格したとしてもOmgzlookは無料で問題集を更新してあげます。
MLS-C01試験概要試験はAmazonのひとつの認証試験でIT業界でとても歓迎があって、ますます多くの人がMLS-C01試験概要「AWS Certified Machine Learning - Specialty」認証試験に申し込んですがその認証試験が簡単に合格できません。準備することが時間と労力がかかります。でも、Omgzlookは君の多くの貴重な時間とエネルギーを節約することを助けることができます。
Amazon MLS-C01試験概要 - ここには、私たちは君の需要に応じます。
弊社のAmazon MLS-C01試験概要問題集を使用した後、MLS-C01試験概要試験に合格するのはあまりに難しくないことだと知られます。我々Omgzlook提供するMLS-C01試験概要問題集を通して、試験に迅速的にパースする技をファンドできます。あなたのご遠慮なく購買するために、弊社は提供する無料のAmazon MLS-C01試験概要問題集デーモをダウンロードします。
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MLS-C01 PDF DEMO:
QUESTION NO: 1
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: 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 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: 4
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: 5
A Machine Learning Specialist receives customer data for an online shopping website. The data includes demographics, past visits, and locality information. The Specialist must develop a machine learning approach to identify the customer shopping patterns, preferences and trends to enhance the website for better service and smart recommendations.
Which solution should the Specialist recommend?
A. A neural network with a minimum of three layers and random initial weights to identify patterns in the customer database
B. Random Cut Forest (RCF) over random subsamples to identify patterns in the customer database
C. Latent Dirichlet Allocation (LDA) for the given collection of discrete data to identify patterns in the customer database.
D. Collaborative filtering based on user interactions and correlations to identify patterns in the customer database
Answer: D
Microsoft MB-230 - IT職員のあなたは毎月毎月のあまり少ない給料を持っていますが、暇の時間でひたすら楽しむんでいいですか。 Microsoft PL-500-CN - 我々の誠意を信じてください。 私たちのJuniper JN0-223試験問題を利用し、ほかの資料が克服できない障害を克服できます。 自分のIT業界での発展を希望したら、AmazonのSASInstitute A00-415試験に合格する必要があります。 Microsoft PL-300 - OmgzlookはきみのIT夢に向かって力になりますよ。
Updated: May 28, 2022