Goldmile-Infobizが提供したAmazonのAWS-Certified-Machine-Learning-Specialty独学書籍「AWS Certified Machine Learning - Specialty」試験問題と解答が真実の試験の練習問題と解答は最高の相似性があり、一年の無料オンラインの更新のサービスがあり、100%のパス率を保証して、もし試験に合格しないと、弊社は全額で返金いたします。 それは君の文化知識を増強でき、君の実践水準も増強でき、君をIT業種での本当のエリートになって、君に他人に羨ましい給料のある仕事をもたらすことができます。うちのAmazonのAWS-Certified-Machine-Learning-Specialty独学書籍試験トレーニング資料を購入する前に、Goldmile-Infobizのサイトで、一部分のフリーな試験問題と解答をダンロードでき、試用してみます。 Goldmile-Infobizは素早く君のAmazon試験に関する知識を補充できて、君の時間とエネルギーが節約させるウェブサイトでございます。
AWS Certified Machine Learning AWS-Certified-Machine-Learning-Specialty もちろんです。
弊社のAmazonのAWS-Certified-Machine-Learning-Specialty - AWS Certified Machine Learning - Specialty独学書籍真題によって、資格認定証明書を受け取れて、仕事の昇進を実現できます。 現在の仕事に満足していますか。自分がやっていることに満足していますか。
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Amazon AWS-Certified-Machine-Learning-Specialty独学書籍 - 信じられなら利用してみてください。
顧客様と販売者の間での信頼性は苦労かつ大切なことだと良く知られます。誠意をみなぎるAmazon AWS-Certified-Machine-Learning-Specialty独学書籍試験備考資料は我々チームの専業化を展示されるし、最完全の質問と再詳細の解説でもって試験に合格するのを助けるます。同時的に、皆様の認可は我々仕事の一番良い評価です。
Goldmile-InfobizのAWS-Certified-Machine-Learning-Specialty独学書籍問題集は多くのIT専門家の数年の経験の結晶で、高い価値を持っています。そのAWS-Certified-Machine-Learning-Specialty独学書籍参考資料はIT認定試験の準備に使用することができるだけでなく、自分のスキルを向上させるためのツールとして使えることもできます。
AWS-Certified-Machine-Learning-Specialty PDF DEMO:
QUESTION NO: 1
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: 2
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: 3
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: 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 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
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Updated: May 28, 2022