Goldmile-InfobizのAmazonのMLS-C01試験解説問題試験トレーニング資料の値段は手頃で、IT認証の受験生のみなさんによく適用します。Goldmile-InfobizのAmazonのMLS-C01試験解説問題試験資料は同じシラバスに従って研究されたのです。それに、資料もずっとアップグレードしていますから、実際の試験問題とよく似ています。 がAmazonのMLS-C01試験解説問題「AWS Certified Machine Learning - Specialty」認定試験の合格書を取ったら仕事の上で大きな変化をもたらします。AmazonのMLS-C01試験解説問題認定試験の最新教育資料はGoldmile-Infobizの専門チームが研究し続けてついに登場し、多くの人の夢が実現させることができます。 試験に準備するときにはあまり多くの時間を無駄にすることを避けるように、Goldmile-Infobizは短時間の勉強をするだけで試験に合格することができるMLS-C01試験解説問題問題集が用意されています。
AWS Certified Specialty MLS-C01 Goldmile-Infobizを選んび、成功を選びます。
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Goldmile-InfobizのAmazonのMLS-C01試験解説問題「AWS Certified Machine Learning - Specialty」試験トレーニング資料はIT職員としてのあなたがIT試験に受かる不可欠なトレーニング資料です。Goldmile-InfobizのAmazonのMLS-C01試験解説問題試験トレーニング資料はカバー率が高くて、更新のスピードも速くて、完全なトレーニング資料ですから、Goldmile-Infobiz を手に入れたら、全てのIT認証が恐くなくなります。人生には様々な選択があります。
Amazon MLS-C01試験解説問題 - いろいろな受験生に通用します。
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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 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: 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 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
QUESTION NO: 5
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
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Updated: May 28, 2022