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NEW QUESTION: 1
Brown works for an investment counseling firm. Green, a new client of the firm, is meeting with Brown for the first time. Green used another counseling firm for financial advice for years, but she has switched her account to Brown's firm. After a few minutes of get-acquainted talk, Brown explained to Green that she has discovered a highly undervalued stock that offers large potential gains. She recommends that Green purchase the stock. Brown has committed a violation of the Standards. What should she have done differently?
A. Brown should have determined Green's needs, objectives and tolerance for risk before making a recommendation for any type of security.
B. Brown should have explained her qualifications, including her education, training, experience and the meaning of the CFA designation.
C. Brown should have asked Green her reasons for changing counseling firms. If the discovery process indicated that Green had been treated unfairly at the other firm, Brown should have notified AIMR of any violation.
D. Brown should have thoroughly explained the characteristics of the company to Green, including the characteristics of the industry in which the company operates.
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Brown has provided investment recommendation before making inquiries about the client's financial situation, investment experience or investment objectives. Brown is thus violating Standard IV (B.2), Portfolio Investment Recommendations and Actions. Why the client changed investment firms is not useful information to provide suitable recommendations. The other answers indicate information members should discuss with their clients at the outset of the relationship, but these answers do not constitute a complete list of those factors.

NEW QUESTION: 2
A company is implementing MFA for all applications that store sensitive data. The IT manager wants MFA to be non-disruptive and user friendly. Which of the following technologies should the IT manager use when implementing MFA?
A. Push notifications
B. One-time passwords
C. Email tokens
D. Hardware authentication
Answer: A

NEW QUESTION: 3
Which of the following tools from AWS allows the automatic collection of software inventory from EC2
instances and helps apply OS patches.
A. EC2AMI's
B. AWSCode Pipeline
C. AWSCode Deploy
D. EC2Systems Manager
Answer: D
Explanation:
Explanation
The Amazon CC2 Systems Manager helps you automatically collect software inventory, apply OS patches,
create system images, and configure Windows and Linux operating systems. These capabilities enable
automated configuration and ongoing management of systems at scale, and help maintain software compliance
for instances running in Amazon L~C2 or on-premises.
One feature within Systems Manager is Automation, which can be used to patch, update agents, or bake
applications into an Amazon Machine Image (AMI). With
Automation, you can avoid the time and effort associated with manual image updates, and instead build AMIs
through a streamlined, repeatable, and auditable process.
For more information on EC2 Systems manager, please refer to the below link:
*
https://aws.amazon.com/blogs/aws/streamline-ami-maintenance-and-patching-using-amazon-ec2-systems-manag

NEW QUESTION: 4
You have a real-time scoring pattern that uses deep learning models in Azure.
You need to complete the scoring pattern.
What should you use? To answer, drag the appropriate Azure services to the correct locations in the scoring pattern. Each service may be used once, more than once, or not at all. You may need to drag the split bat between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: Azure Container Registry
Azure Container Registry enables storage of images for all types of Docker container deployments including DC/OS, Docker Swarm and Kubernetes. The scoring images are deployed as containers on Azure Kubernetes Service and used to run the scoring script. The image used here is created by Machine Learning from the trained model and scoring script, and then is pushed to the Azure Container Registry.
Box 2: Azure Kubernetes Services
Azure Kubernetes Service (AKS) is used to deploy the application on a Kubernetes cluster. AKS simplifies the deployment and operations of Kubernetes. The cluster can be configured using CPU-only VMs for regular Python models or GPU-enabled VMs for deep learning models.
This reference architecture shows how to deploy Python models as web services to make real-time predictions using the Azure Machine Learning.

References:
https://docs.microsoft.com/sv-se/azure/architecture/reference-architectures/ai/realtime-scoring-python