Databricks-Certified-Professional-Data-Scientist無料問題集「Databricks Certified Professional Data Scientist」

質問 1

RMSE measures error of a predicted

（A）For booth Numerical and categorical values

（B）Categorical values

（C）Numerical Value

正解：C 解答を投票する

質問 2

Question-3: In machine learning, feature hashing, also known as the hashing trick (by analogy to the kernel trick), is a fast and space-efficient way of vectorizing features (such as the words in a language), i.e., turning arbitrary features into indices in a vector or matrix. It works by applying a hash function to the features and using their hash values modulo the number of features as indices directly, rather than looking the indices up in an associative array. So what is the primary reason of the hashing trick for building classifiers?

（A）It creates the smaller models

（B）It reduces the non-significant features e.g. punctuations

（C）It requires the lesser memory to store the coefficients for the model

（D）Noisy features are removed

正解：C 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 3

You are analyzing data in order to build a classifier model. You discover non-linear data and discontinuities that will affect the model. Which analytical method would you recommend?

（A）Logistic Regression

（B）Decision Trees

（C）ARIMA

（D）Linear Regression

正解：B 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 4

Which method is used to solve for coefficients bO, b1, ... bn in your linear regression model:

（A）Apriori Algorithm

（B）Ridge and Lasso

（C）Ordinary Least squares

（D）Integer programming

正解：C 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 5

What type of output generated in case of linear regression?

（A）Continuous variable

（B）Any of the Continuous and Discrete variable

（C）Discrete Variable

（D）Values between 0 and 1

正解：A 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 6

Select the correct option which applies to L2 regularization

（A）Computational efficient due to having analytical solutions

（B）No feature selection

（C）Non-sparse outputs

正解：A、B、C 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 7

While working with Netflix the movie rating websites you have developed a recommender system that has produced ratings predictions for your data set that are consistently exactly 1 higher for the user-item pairs in your dataset than the ratings given in the dataset. There are n items in the dataset. What will be the calculated RMSE of your recommender system on the dataset?

（A）n/2

（B）1

（C）2

（D）0

正解：B 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 8

What is one modeling or descriptive statistical function in MADlib that is typically not provided in a standard relational database?

（A）Quantiles

（B）Linear regression

（C）Variance

（D）Expected value

正解：B 解答を投票する

質問 9

The figure below shows a plot of the data of a data matrix M that is 1000 x 2. Which line represents the first principal component?

（A）Neither

（B）blue

（C）yellow

正解：B 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 10

A denote the event 'student is female' and let B denote the event 'student is French'. In a class of 100 students suppose 60 are French, and suppose that 10 of the French students are females. Find the probability that if I pick a French student, it will be a girl, that is, find P(A|B).

（A）1/3

（B）2/3

（C）2/6

（D）1/6

正解：D 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

Databricks-Certified-Professional-Data-Scientist 無料問題集「Databricks Certified Professional Data Scientist」

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