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

質問 1

You are designing a recommendation engine for a website where the ability to generate more personalized recommendations by analyzing information from the past activity of a specific user, or the history of other users deemed to be of similar taste to a given user. These resources are used as user profiling and helps the site recommend content on a user-by-user basis. The more a given user makes use of the system, the better the recommendations become, as the system gains data to improve its model of that user. What kind of this recommendation engine is ?

（A）Logistic Regression

（B）Collaborative filtering

（C）Naive Bayes classifier

（D）Content-based filtering

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 2

Which of the following is a Continuous Probability Distributions?

（A）Binomial probability distribution

（B）Normal probability distribution

（C）Poisson probability distribution

（D）Negative binomial distribution

正解：B 解答を投票する

質問 3

A bio-scientist is working on the analysis of the cancer cells. To identify whether the cell is cancerous or not, there has been hundreds of tests are done with small variations to say yes to the problem. Given the test result for a sample of healthy and cancerous cells, which of the following technique you will use to determine whether a cell is healthy?

（A）Collaborative filtering

（B）Linear regression

（C）Naive Bayes

（D）Identification Test

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 4

You have data of 10.000 people who make the purchasing from a specific grocery store. You also have their income detail in the data. You have created 5 clusters using this data. But in one of the cluster you see that only 30 people are falling as below 30, 2400, 2600, 2700, 2270 etc." What would you do in this case?

（A）You will be decreasing the number of clusters.

（B）You will remove that 30 people from dataset

（C）You will be increasing number of clusters.

（D）You will be multiplying standard deviation with the 100

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 5

RMSE is a good measure of accuracy, but only to compare forecasting errors of different models for a______, as it is scale-dependent.

（A）Between Variables

（B）Particular Variable

（C）Among all the variables

（D）All of the above are correct

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 6

Refer to Exhibit

In the exhibit, the x-axis represents the derived probability of a borrower defaulting on a loan. Also in the exhibit, the pink represents borrowers that are known to have not defaulted on their loan, and the blue represents borrowers that are known to have defaulted on their loan. Which analytical method could produce the probabilities needed to build this exhibit?

（A）Association Rules

（B）Logistic Regression

（C）Discriminant Analysis

（D）Linear Regression

正解：B 解答を投票する

質問 7

Regularization is a very important technique in machine learning to prevent overfitting. Mathematically speaking, it adds a regularization term in order to prevent the coefficients to fit so perfectly to overfit. The difference between the L1 and L2 is...

（A）L1 is the sum of the square of the weights, while L2 is just the sum of the weights

（B）L2 is the sum of the square of the weights, while L1 is just the sum of the weights

（C）None of the above

（D）L1 gives Non-sparse output while L2 gives sparse outputs

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

Which of the following technique can be used to the design of recommender systems?

（A）Collaborative filtering

（B）2 and 3

（C）1 and 3

（D）Naive Bayes classifier

（E）Power iteration

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 9

Your customer provided you with 2. 000 unlabeled records three groups. What is the correct analytical method to use?

（A）K-means clustering

（B）Linear regression

（C）Logistic regression

（D）Semi Linear Regression

（E）Naive Bayesian classification

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 10

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)

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

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