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NEW QUESTION: 1
You have a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features.
You use 75 percent of the data points for training and 25 percent for testing. You are using the scikit-learn machine learning library in Python. You use X to denote the feature set and Y to denote class labels.
You create the following Python data frames:

You need to apply the Principal Component Analysis (PCA) method to reduce the dimensionality of the feature set to 10 features in both training and testing sets.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: PCA(n_components = 10)
Need to reduce the dimensionality of the feature set to 10 features in both training and testing sets.
Example:
from sklearn.decomposition import PCA
pca = PCA(n_components=2) ;2 dimensions
principalComponents = pca.fit_transform(x)
Box 2: pca
fit_transform(X[, y])fits the model with X and apply the dimensionality reduction on X.
Box 3: transform(x_test)
transform(X) applies dimensionality reduction to X.
References:
https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html

NEW QUESTION: 2
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution. Determine whether the solution meets the stated goals.
You develop an entertainment application where users can buy and trade virtual real estate. The application must scale to support thousands of users.
The current architecture includes five Azure Virtual Machines (VM) that connect to an Azure SQL Database for account information and Azure Table Storage for backend services. A user interacts with these components in the cloud at any given time
- Routing Service - Routes a request to the appropriate service and must not persist data across sessions
- Account Service - Stores and manages all account information and authentication and requires data to persist across sessions.
- User Service - Stores and manages all user information and requires data to persist across sessions.
- Housing Network Service - Stores and manages the current real-estate economy and requires data to persist across sessions.
- Trade Service - Stores and manages virtual trade between accounts and requires data to persist across sessions.
Due to volatile user traffic, a microservices solution is selected for scale agility.
You need to migrate to a distributed microservices solution on Azure Service Fabric.
Solution: Create a Service Fabric Cluster with a stateless Reliable Service for Routing Service. Create stateful Reliable Services for all other components.
Does the solution meet the goal?
A. No
B. Yes
Answer: B
Explanation:
Explanation/Reference:
Explanation:
We should use stateful services when we want data to persist, and stateless service when data must not persist.
Note:
For stateful services, the Reliable Services programming model allows you to consistently and reliably store your state right inside your service by using Reliable Collections.
A stateless service is one where there is no state maintained within the service across calls. Any state that is present is entirely disposable and doesn't require synchronization, replication, persistence, or high availability.
References:
https://docs.microsoft.com/en-us/azure/service-fabric/service-fabric-reliable-services-introduction

NEW QUESTION: 3
Which of the following are included in the template object?
A. ui.json
B. A,B and C
C. app.json
D. A,C
E. variables.json
Answer: D
Explanation:
* template-info.json manages all elements of your template, including metadata information about the template, the Analytics objects that define dashboards and lenses, and the other files that are part of the template. * ui.json manages the configuration wizard that drives app creation. It defines the number of wizard pages, the order of wizard questions, and any messages you want the user to see. * variables.json contains all template variables, including text for wizard questions and specifications for the answers. Variables also define conditional questions. For example, you may want some questions to appear in the wizard only if an org contains certain data. Or you might want to add more specific questions based on the answers to more general wizard questions. * template-to-app-rules.json defines the rules the template follows. For example, you could define a rule that specifies that if an org doesn't use certain Salesforce objects, the app won't refer to them in dashboards or include them in the dataflow. Rules also define how variables are handled. For example, if the wizard asks which fields to include in filters for accounts, template-to-app-rules.json determines how that choice is reflected in dashboards.