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## Dell Technologies D-AA-OP-23 Sample Questions:

**01. You conduct a TFIDF analysis on 3 documents containing raw text and derive TFIDF ("data", document y) = 1.908. You know that the term "data” only appears in document 2.**

**What is the TF of “data" in document 2?**

**a)**2 based on the following reasoning: TFIDF = TF1DF = 1 908 You then know that IDF will equal LOG (32)=0.954 Therefore, TFIDF=TF*0.954 = 1.908 TF will then round to 2

**b)**4 based on the following reasoning: TFIDF = TF1DF = 1.908 You then know that IDF will equal LOG (3/1 )=0.477 Therefore, TFIDF=TF'0 477 = 1.908 TF will then round to 4

**c)**6 based on the following reasoning: TFIDF = TF1DF = 1.908 You then know that IDF will equal 3/1=3 Therefore, TFIDF=TF/3 = 1.908 TF will then round to 6

**d)**11 based on the following reasoning: TFIDF = TF1DF = 1908 You then know that IDF will equal LOG(3/2)=0.176 Therefore, TFIDF=TF"0.176 = 1.908 TF will then round to 11

**02. Which scenario is a proper use case for multinomial logistic regression?**

**a)**A marketing firm wants to estimate the personal income of a group of potential customers. Using inputs such as age, education, marital status, and credit card expenditures, a data scientist is building a model that will estimate a person's income

**b)**A logistic distribution company wants to minimize the distance traveled by its delivery trucks. A data scientist is building a model to determine the optimal route for each of tis trucks

**c)**To improve the initial routing of a loan application, a financial institution plans to classify a loan application as Approve, Reject, or Possibly_Approve. Based on the company's historical loan application data, a data scientist is building a model to assign one of these three outcomes to each submitted application.

**d)**A manufacturer plans to determine the optimal number of workers to employ in an assembly line process. Utilizing the observed distributions of the task durations of each process step, a data scientist is building a model to mimic the interactions and dependencies between each stage in the manufacturing process.

**03. You are analyzing written transcripts of focus groups conducted on product X. You approach is to use TF-IDF for your analysis.**

**What combination of TF-IDF scores should you examine to ensure you only report on the most important terms?**

**a)**High TF score and high DF score

**b)**High TF score and high IDF score

**c)**High TF score and low IDF score

**d)**Low TF score and low DF score

**04. Why would a company decide to use HBase to replace an existing relational database?**

**a)**It is required for performing ad-hoc queries.

**b)**Varying formats of input data requires columns to be added in real time.

**c)**The company's employees are already fluent in SQL.

**d)**Existing SQL code will run unchanged on HBase.

**05. What is a characteristic of stop words?**

**a)**Meaningful words requiring a parser to stop and examine them

**b)**Don't occur often in text

**c)**Used in term frequency analysis

**d)**Include words such as "a", "an", and "the"

**06.**

**According to Metcalfe's law, what is true about the value of a network?**

**a)**Proportional to the number of edges

**b)**Proportional to the logarithm of the number of edges

**c)**Unrelated to the number of edges

**d)**Proportional to the square of the number of edges

**07.**

**Which problem type is best suited for simulation?**

**a)**One with a few. non-random input variables

**b)**One that compares "what-if scenarios

**c)**One with numerous, non-random Input-variables

**d)**One that has a closed-form solution

**08. You develop a Python script "logisticpy" to evaluate the logistic function denoted as f(y) for a given value y that includes the following Pig code:**

**What is the expected output when the Pig code is executed?**

**a)**0

**b)**Jython is not a supported language

**c)**Value of f(y) for ally

**d)**Tuples (y, f(y))

**09. Which scenario would be ideal for processing Hadoop data with Hive?**

**a)**Unstructured data; batch processing

**b)**Structured data, real-time processing

**c)**Structured data; batch processing

**d)**Unstructured data; real-time processing

**10. What are key characteristics of Random Graphs?**

**a)**Low clustering coefficients; high network diameters

**b)**Low clustering coefficients; small network diameters

**c)**High clustering coefficients; high network diameters

**d)**High clustering coefficients; small network diameters

## Answers:

Question: 1 | Answer: b | Question: 2 | Answer: c |

Question: 3 | Answer: c | Question: 4 | Answer: a |

Question: 5 | Answer: d | Question: 6 | Answer: c |

Question: 7 | Answer: b | Question: 8 | Answer: d |

Question: 9 | Answer: a | Question: 10 | Answer: b |

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