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[October-2021]MLS-C01 PDF and MLS-C01 VCE Dumps MLS-C01 181Q Instant Download in Braindump2go[Q158-Q171]

October/2021 Latest Braindump2go MLS-C01 Exam Dumps with PDF and VCE Free Updated Today! Following are some new MLS-C01 Real Exam Questions!

QUESTION 158
A company needs to quickly make sense of a large amount of data and gain insight from it. The data is in different formats, the schemas change frequently, and new data sources are added regularly. The company wants to use AWS services to explore multiple data sources, suggest schemas, and enrich and transform the data. The solution should require the least possible coding effort for the data flows and the least possible infrastructure management.
Which combination of AWS services will meet these requirements?

A. Amazon EMR for data discovery, enrichment, and transformation
Amazon Athena for querying and analyzing the results in Amazon S3 using standard SQL
Amazon QuickSight for reporting and getting insights
B. Amazon Kinesis Data Analytics for data ingestion
Amazon EMR for data discovery, enrichment, and transformation
Amazon Redshift for querying and analyzing the results in Amazon S3
C. AWS Glue for data discovery, enrichment, and transformation
Amazon Athena for querying and analyzing the results in Amazon S3 using standard SQL
Amazon QuickSight for reporting and getting insights
D. AWS Data Pipeline for data transfer
AWS Step Functions for orchestrating AWS Lambda jobs for data discovery, enrichment, and transformation
Amazon Athena for querying and analyzing the results in Amazon S3 using standard SQL
Amazon QuickSight for reporting and getting insights

Answer: A

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[November-2020]MLS-C01 Dumps Free Download in Braindump2go[Q82-Q102]

November/2020 Latest Braindump2go MLS-C01 Exam Dumps with PDF and VCE Free Updated Today! Following are some new MLS-C01 Real Exam Questions!

QUESTION 82
A Data Scientist is building a model to predict customer churn using a dataset of 100 continuous numerical features. The Marketing team has not provided any insight about which features are relevant for churn prediction. The Marketing team wants to interpret the model and see the direct impact of relevant features on the model outcome. While training a logistic regression model, the Data Scientist observes that there is a wide gap between the training and validation set accuracy.
Which methods can the Data Scientist use to improve the model performance and satisfy the Marketing team’s needs? (Choose two.)

A. Add L1 regularization to the classifier
B. Add features to the dataset
C. Perform recursive feature elimination
D. Perform t-distributed stochastic neighbor embedding (t-SNE)
E. Perform linear discriminant analysis

Answer: BE

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