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選擇Goldmile-Infobiz為你提供的針對性培訓，你可以很輕鬆通過Amazon MLS-C01 - AWS Certified Machine Learning - Specialty題庫更新 認證考試。 Goldmile-Infobiz已經獲得了很多認證行業的聲譽，因為我們有很多的Amazon的最新 MLS-C01 題庫資源考古題，最新 MLS-C01 題庫資源學習指南，最新 MLS-C01 題庫資源考古題，最新 MLS-C01 題庫資源考題答案，目前在網站上作為最專業的IT認證測試供應商，我們提供完善的售後服務，我們給所有的客戶買的跟蹤服務，在你購買的一年，享受免費的升級試題服務，如果在這期間，認證測試中心Amazon的最新 MLS-C01 題庫資源試題顯示修改或者別的，我們會提供免費為客戶保護，顯示Amazon的最新 MLS-C01 題庫資源考試認證是由我們Goldmile-Infobiz的IT產品專家精心打造，有了Goldmile-Infobiz的Amazon的最新 MLS-C01 題庫資源考試資料，相信你的明天會更好。
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Amazon MLS-C01題庫更新 - 來吧，你將是未來最棒的IT專家。
Goldmile-Infobiz是領先于世界的學習資料提供商之一，您可以下載我們最新的PDF版本免費試用作為體驗。我們還提供可靠和有效的軟件版本MLS-C01題庫更新題庫資料，幫助您模擬真實的考試環境，以方便考生掌握最新的Amazon MLS-C01題庫更新考試資訊。在我們的指導和幫助下，可以首次通過您的考試，MLS-C01題庫更新考古題是IT專家經過實踐測試得到的，MLS-C01題庫更新考古題也能幫您在IT行業的未來達到更高的水平。
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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