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NEW QUESTION 42
Which method is used to solve for coefficients bO, b1, … bn in your linear regression model:

  • A. Integer programming
  • B. Ridge and Lasso
  • C. Apriori Algorithm
  • D. Ordinary Least squares

Answer: D

Explanation:
Explanation : RY = b0 + b1x1+b2x2+ …. +bnxn
In the linear model, the bi’s represent the unknown p parameters. The estimates for these unknown parameters
are chosen so that, on average, the model provides a reasonable estimate of a person’s income based on age
and education. In other words, the fitted model should minimize the overall error between the linear model and
the actual observations. Ordinary Least Squares (OLS) is a common technique to estimate the parameters

 

NEW QUESTION 43
A dataset has been defined using Delta Live Tables and includes an expectations clause:
1. CONSTRAINT valid_timestamp EXPECT (timestamp > ‘2020-01-01’)
What is the expected behaviour when a batch of data containing data that violates these constraints is
processed?

  • A. Records that violate the expectation are dropped from the target dataset and recorded as invalid in the event log
  • B. Records that violate the expectation cause the job to fail
  • C. Records that violate the expectation are added to the target dataset and recorded as invalid in the event log
  • D. Records that violate the expectation are added to the target dataset and flagged as in-valid in a field added to the target dataset
  • E. Records that violate the expectation are dropped from the target dataset and loaded into a quarantine table

Answer: C

 

NEW QUESTION 44
A data engineer has ingested a JSON file into a table raw_table with the following schema:
1.transaction_id STRING,
2.payload ARRAY<customer_id:STRING, date:TIMESTAMP, store_id:STRING>
The data engineer wants to efficiently extract the date of each transaction into a table with the fol-lowing
schema:
1.transaction_id STRING,
2.date TIMESTAMP
Which of the following commands should the data engineer run to complete this task?

  • A. 1.SELECT transaction_id, date from payload
    2.FROM raw_table;
  • B. 1.SELECT transaction_id, explode(payload)
    2.FROM raw_table;
  • C. 1.SELECT transaction_id, payload.date
    2.FROM raw_table;
  • D. 1.SELECT transaction_id, date
    2.FROM raw_table;
  • E. 1.SELECT transaction_id, payload[date]
    2.FROM raw_table;

Answer: C

 

NEW QUESTION 45
A data architect has determined that a table of the following format is necessary:
Which of the following code blocks uses SQL DDL commands to create an empty Delta table in the above
format regardless of whether a table already exists with this name?

  • A. 1. CREATE OR REPLACE TABLE table_name
    2. WITH COLUMNS ( id STRING, birthDate DATE, avgRating FLOAT ) USING DELTA
  • B. 1. CREATE OR REPLACE TABLE table_name AS
    2. SELECT id STRING, birthDate DATE, avgRating FLOAT USING DELTA
  • C. 1. CREATE OR REPLACE TABLE table_name ( id STRING, birthDate DATE, avgRating FLOAT )
  • D. 1. CREATE TABLE IF NOT EXISTS table_name ( id STRING, birthDate DATE, avgRating FLOAT )
  • E. 1. CREATE TABLE table_name AS
    2. SELECT id STRING, birthDate DATE, avgRating FLOAT

Answer: C

 

NEW QUESTION 46
Suppose there are three events then which formula must always be equal to P(E1|E2,E3)?

  • A. P(E1,E2,E3)P(E1)/P(E2:E3)
  • B. P(E1,E2;E3)/P(E2,E3)
  • C. P(E1,E2,E3)P(E2)P(E3)
  • D. P(E1,E2|E3)P(E2|E3)P(E3)
  • E. P(E1,E2|E3)P(E3)

Answer: B

Explanation:
Explanation
This is an application of conditional probability: P(E1,E2)=P(E1|E2)P(E2). so
P(E1|E2) = P(E1.E2)/P(E2)
P(E1,E2,E3)/P(E2,E3)
If the events are A and B respectively, this is said to be “the probability of A given B”
It is commonly denoted by P(A|B):or sometimes PB(A). In case that both “A” and “B” are categorical
variables, conditional probability table is typically used to represent the conditional probability.

 

NEW QUESTION 47
……

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