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NEW QUESTION 34
Which method is used to solve for coefficients bO, b1, ... bn in your linear regression model:
Answer: C
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 35
A new data engineer has started at a company. The data engineer has recently been added to the company's
Databricks workspace as [email protected]. The data engineer needs to be able to query the table
sales in the database retail. The new data engineer already has been granted USAGE on the database retail.
Which of the following commands can be used to grant the appropriate permissions to the new data engineer?
Answer: D
NEW QUESTION 36
Projecting a multi-dimensional dataset onto which vector has the greatest variance?
Answer: B
Explanation:
Explanation
The method based on principal component analysis (PCA) evaluates the features according to the projection of
the largest eigenvector of the correlation matrix on the initial dimensions, the method based on Fisher's linear
discriminant analysis evaluates. Them according to the magnitude of the components of the discriminant
vector.
The first principal component corresponds to the greatest variance in the data, by definition. If we project the
data onto the first principal component line, the data is more spread out (higher variance) than if projected onto
any other line, including other principal components.
NEW QUESTION 37
Which of the following Structured Streaming queries is performing a hop from a Bronze table to a Silver
table?
2. .withColumn("avgPrice", col("sales") / col("units"))
3. .writeStream
4. .option("checkpointLocation", checkpointPath)
5. .outputMode("append")
6. .table("cleanedSales")
7.)B. 1. (spark.readStream.load(rawSalesLocation)
2. .writeStream
3. .option("checkpointLocation", checkpointPath)
4. .outputMode("append")
5. .table("uncleanedSales")
6. )C. 1. (spark.read.load(rawSalesLocation)
2. .writeStream
3. .option("checkpointLocation", checkpointPath)
4. .outputMode("append")
5. .table("uncleanedSales")
6. )D. 1. (spark.table("sales")
2. .agg(sum("sales"),
3. sum("units"))
4. .writeStream
5. .option("checkpointLocation", checkpointPath)
6. .outputMode("complete")
7. .table("aggregatedSales")
8. )E. 1. (spark.table("sales")
2. .groupBy("store")
3. .agg(sum("sales"))
4. .writeStream
5. .option("checkpointLocation", checkpointPath)
6. .outputMode("complete")
7. .table("aggregatedSales")
8.)
Answer: A
NEW QUESTION 38
......
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