Goldmile-Infobizは合格率が１００パーセントということを保証します。Goldmile-Infobizというサイトには全的な資源とAmazonのMLS-C01勉強時間の試験問題があります。それに、AmazonのMLS-C01勉強時間の試験の実践経験やテストダンプにも含まれています。 弊社が提供したすべての勉強資料と他のトレーニング資料はコスト効率の良い製品で、サイトが一年間の無料更新サービスを提供します。ですから、弊社のトレーニング製品はあなたが試験に合格することを助けにならなかったら、全額で返金することを保証します。 そうすると、Goldmile-InfobizのAmazonのMLS-C01勉強時間トレーニング資料の品質をよく知っています。
AWS Certified Specialty MLS-C01 ここにはあなたが最も欲しいものがありますから。
AWS Certified Specialty MLS-C01勉強時間 - AWS Certified Machine Learning - Specialty 空想は人間が素晴らしいアイデアをたくさん思い付くことができますが、行動しなければ何の役に立たないのです。 そうすれば、実際のMLS-C01 対応受験試験を受けるときに緊張をすることはないです。ですから、心のリラックスした状態で試験に出る問題を対応することができ、あなたの正常なレベルをプレイすることもできます。
今教えてあげますよ。Goldmile-InfobizのMLS-C01勉強時間問題集を利用することです。AmazonのMLS-C01勉強時間認定試験は現在で本当に人気がある試験ですね。
AmazonのAmazon MLS-C01勉強時間認定試験を受験する気があるのですか。
Goldmile-Infobizは君の成功のために、最も質の良いAmazonのMLS-C01勉強時間試験問題と解答を提供します。もし君はいささかな心配することがあるなら、あなたはうちの商品を購入する前に、Goldmile-Infobizは無料でサンプルを提供することができます。あなたはGoldmile-InfobizのAmazonのMLS-C01勉強時間問題集を購入した後、私たちは一年間で無料更新サービスを提供することができます。
この問題集は的中率が高くて、あなたの一発成功を保証できますから。ほかの試験参考書より、この問題集はもっと正確に実際問題の範囲を絞ることができます。
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