試験に受かるために大量の時間とトレーニング費用を費やした受験生がたくさんいます。ここで我々は良い学習資料のウェブサイトをお勧めします。Goldmile-Infobizというサイトです。 そして、試験を安心に参加してください。Goldmile-InfobizのIT業界専門家チームは彼らの経験と知識を利用して絶えないな試験対策材料の品質を高めて、受験者の需要を満たして、受験者のはじめてAmazon MLS-C01復習テキスト試験を順調に合格するを保証します。 現在、書籍の以外にインターネットは知識の宝庫として見られています。
AWS Certified Specialty MLS-C01 あなたは勇敢な人ですか。
AWS Certified Specialty MLS-C01復習テキスト - AWS Certified Machine Learning - Specialty 弊社は君の試験に合格させるとともにまた一年の無料の更新のサービスも提供し、もし試験に失敗したら全額で返金いたします。 もちろん、IT業界で働いているあなたはIT認定試験を受けて資格を取得することは一番良い選択です。それはより良く自分自身を向上させることができますから。
この情報の時代には、IT業界にとても注目され、この強い情報技術業界にIT人材が得難いです。こうしてAmazon認定試験がとても重要になります。でも、この試験がとても難しくてIT者になりたい方が障害になっています。
彼らにAmazonのAmazon MLS-C01復習テキスト試験に合格させました。
現在、市場でオンラインのAmazonのMLS-C01復習テキスト試験トレーニング資料はたくさんありますが、Goldmile-InfobizのAmazonのMLS-C01復習テキスト試験トレーニング資料は絶対に最も良い資料です。我々Goldmile-Infobizはいつでも一番正確なAmazonのMLS-C01復習テキスト資料を提供するように定期的に更新しています。それに、Goldmile-InfobizのAmazonのMLS-C01復習テキスト試験トレーニング資料が一年間の無料更新サービスを提供しますから、あなたはいつも最新の資料を持つことができます。
何十ユーロだけでこのような頼もしいAmazonのMLS-C01復習テキスト試験の資料を得ることができます。試験に合格してからあなたがよりよい仕事と給料がもらえるかもしれません。
MLS-C01 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