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D-DS-FN-23 Latest Braindumps Book - Exam D-DS-FN-23 Answers

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EMC D-DS-FN-23 Exam Syllabus Topics:

Topic
Details

Topic 1

Initial Analysis of the Data: This section of the exam measures the skills of a Data Science Enthusiast and focuses on the first steps in analyzing data. It explains how basic R commands are used for exploration, discusses important statistical measures and visualizations, and describes hypothesis testing techniques for evaluating models.

Topic 2

Data Analytics Lifecycle: This section of the exam measures the skills of an Entry-Level Data Analyst and explains the purpose and phases of the data analytics lifecycle. It includes understanding key activities and roles involved in the discovery, data preparation, model planning, and model building phases to successfully manage analytics projects.

Topic 3

Big Data, Analytics, and the Data Scientist Role: This section of the exam measures the skills of a Data Science Enthusiast and covers the basic concepts of Big Data, including its defining characteristics and the business drivers behind its rise. It also introduces the role of the Data Scientist, highlighting the critical skills needed in the data science field.

Topic 4

Operationalizing an Analytics Project and Data Visualization Techniques: This section of the exam measures the skills of an Entry-Level Data Analyst and explains best practices for communicating findings and operationalizing analytics projects. It covers effective methods for presenting projects to various audiences and emphasizes the importance of planning and creating impactful data visualizations.

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EMC Dell Data Science Foundations Sample Questions (Q112-Q117):

NEW QUESTION # 112
You have fit a decision tree classifier using 12 input variables. The resulting tree used 7 of the 12 variables, and is 5 levels deep. Some of the nodes contain only 3 data points. The AUC of the model is 0.85.
What is your evaluation of this model?

A. The AUC is high, so the overall model is accurate. It is not well-calibrated, because the small nodes will give poor estimates of probability.
B. The tree is probably overfit. Try fitting shallower trees and using an ensemble method.
C. The tree did not split on all the input variables. You need a larger data set to get a more accurate model.
D. The AUC is high, and the small nodes are all very pure. This is an accurate model.

Answer: B

NEW QUESTION # 113
You have been assigned to run a linear regression model for each of 5, 000 distinct districts, and all the data is currently stored in a PostgreSQL database.
Which tool/library would you use to produce these models with the least effort?

A. HBase
B. R
C. Mahout
D. MADlib

Answer: D

NEW QUESTION # 114
You have created a Linear Regression model to predict total sales based on variables M, N, P and Q as shown in the graphic. You originally expected all variables to have positive coefficients.

Which action would you take?

A. Accept only statistically significant variables and investigate correlated independent variables
B. Accept all variables and begin model validation steps against holdout data
C. Accept only positive variables and investigate potential correlation with the dependent variable
D. Accept none of the variables and investigate correlations between all variables

Answer: D

NEW QUESTION # 115
You are having a discussion with a business colleague. The colleague mentions that they want to perform K-means clustering on text file data stored in HDFS.
Which tool should be recommended?

A. Scribe
B. HBase
C. Sqoop
D. Mahout

Answer: D

NEW QUESTION # 116
Which component of a final presentation focuses on how to deploy the model?

A. Executive summary
B. Recommendations
C. Project goals
D. Approach

Answer: B

NEW QUESTION # 117
......

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