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

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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

[2020-August-New]Braindump2go SAP-C01 Dumps Free Download SAP-C01 668Q(Q632-Q647)

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QUESTION 632
A company is developing a new service that will be accessed using TCP on a static port. A solutions architect must ensure that the service is highly available, has redundancy across Availability Zones, and is accessible using the DNS name my.service.com, which is publicly accessible. The service must use fixed address assignments so other companies can add the addresses to their allow lists.
Assuming that resources are deployed in multiple Availability Zones in a single Region, which solution will meet these requirements?

A. Create Amazon EC2 instances with an Elastic IP address for each instance.
Create a Network Load Balancer (NLB) and expose the static TCP port.
Register EC2 instances with the NLB.
Create a new name server record set named my.service.com, and assign the Elastic IP addresses of the EC2 instances to the record set.
Provide the Elastic IP addresses of the EC2 instances to the other companies to add to their allow lists.
B. Create an Amazon ECS cluster and a service definition for the application.
Create and assign public IP addresses for the ECS cluster.
Create a Network Load Balancer (NLB) and expose the TCP port.
Create a target group and assign the ECS cluster name to the NLB.
Create a new A record set named my.service.com, and assign the public IP addresses of the ECS cluster to the record set.
Provide the Public IP addresses of the ECS cluster to the other companies to add to their allow lists.
C. Create Amazon EC2 instances for the service.
Create one Elastic IP address for each Availability Zone.
Create a Network Load Balancer (NLB) and expose the assigned TCP port.
Assign the Elastic IP addresses to the NLB for each Availability Zone.
Create a target group and register the EC2 instances with the NLB.
Create a new A (alias) record set named my.service.com, and assign the NLB DNS name to the record set.
D. Create an Amazon ECS cluster and a service definition for the application.
Create and assign public IP address for each host in the cluster.
Create an Application Load Balancer (ALB) and expose the static TCP port.
Create a target group and assign the ECS service definition name to the ALB.
Create a new CNAME record set and associate the public IP addresses to the record set.
Provide the Elastic IP addresses of the Amazon EC2 instances to the other companies to add to their allow lists.

[2020-August-New]Free SAA-C02 SAA-C02 301Q SAA-C02 Dumps PDF and VCE Braindump2go Offer[263-283]

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QUESTION 263
A solutions architect is designing a multi-Region disaster recovery solution for an application that will provide public API access.
The application will use Amazon EC2 instances with a userdata script to load application code and an Amazon RDS for MySQL database.
The Recovery Time Objective (RTO) is 3 hours and the Recovery Point Objective (RPO) is 24 hours.
Which architecture would meet these requirements at the LOWEST cost?

A.    Use an Application Load Balancer for Region failover.
Deploy new EC2 instances with the userdata script.
Deploy separate RDS instances in each Region
B.    Use Amazon Route 53 for Region failover.
Deploy new EC2 instances with the userdata script.
Create a read replica of the RDS instance in a backup Region
C.    Use Amazon API Gateway for the public APIs and Region failover.
Deploy new EC2 instances with the userdata script.
Create a MySQL read replica of the RDS instance in a backup Region
D.    Use Amazon Route 53 for Region failover.
Deploy new EC2 instances with the userdata scnpt for APIs, and create a snapshot of the RDS instance daily for a backup.
Replicate the snapshot to a backup Region

[July-2020]Exam Pass 100%!Braindump2go SAA-C02 Exam Dumps PDF SAA-C02 262Q Instant Download[208-228]

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QUESTION 208
A company is designing a new service that will run on Amazon EC2 instance behind an Elastic Load Balancer.
However, many of the web service clients can only reach IP addresses whitelisted on their firewalls.
What should a solution architect recommend to meet the clients’ needs?

A. A Network Load Balancer with an associated Elastic IP address.
B. An Application Load Balancer with an a associated Elastic IP address
C. An A record in an Amazon Route 53 hosted zone pointing to an Elastic IP address
D. An EC2 instance with a public IP address running as a proxy in front of the load balancer

[2020-April-New]Real Exam Questions-Braindump2go MLS-C01 Exam Dumps PDF and VCE 81Q Download

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New Question
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%, 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 dropout rate at the flatten layer should be increased because the model is not generalized enough.
C. The dimensionality of dense layer next to the flatten layer should be increased because the model is not complex enough.
D. The epoch number should be increased because the optimization process was terminated before it reached the global minimum.