EMT Practice Test

1. Question Content...

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Question1: What Can Snowflake Data Scientist do in the Snowflake Marketplace as Consumer?

Question2: Which is the visual depiction of data through the use of graphs, plots, and informational graphics?

Question3: Which of the Following is not type of Windows function in Snowflake?

Question4: Which one is not Types of Feature Scaling?

Question5: Skewness of Normal distribution is ___________

Question6: Which one is incorrect understanding about Providers of Direct share?

Question7: You previously trained a model using a training dataset. You want to detect any data drift in the new data collected since the model was trained.
What should you do?

Question8: Which ones are the correct rules while using a data science model created via External function in Snowflake?

Question9: Which tools helps data scientist to manage ML lifecycle & Model versioning?

Question10: Which of the following cross validation versions is suitable quicker cross-validation for very large datasets with hundreds of thousands of samples?

Question11: The most widely used metrics and tools to assess a classification model are:

Question12: Select the Data Science Tools which are known to provide native connectivity to Snowflake?

Question13: Which of the following is a common evaluation metric for binary classification?

Question14: Which one is not the feature engineering techniques used in ML data science world?

Question15: Which of the following metrics are used to evaluate classification models?

Question16: Consider a data frame df with 10 rows and index [ 'r1', 'r2', 'r3', 'row4', 'row5', 'row6', 'r7', 'r8', 'r9', 'row10'].
What does the aggregate method shown in below code do?
g = df.groupby(df.index.str.len())
g.aggregate({'A':len, 'B':np.sum})

Question17: Which of the following Snowflake parameter can be used to Automatically Suspend Tasks which are running Data science pipelines after specified Failed Runs?

Question18: Which ones are the key actions in the data collection phase of Machine learning included?

Question19: What is the risk with tuning hyper-parameters using a test dataset?

Question20: Which type of Python UDFs let you define Python functions that receive batches of input rows as Pandas DataFrames and return batches of results as Pandas arrays or Series?

Question21: You are training a binary classification model to support admission approval decisions for a college degree program.
How can you evaluate if the model is fair, and doesn't discriminate based on ethnicity?

Question22: Select the correct mappings:
I. W Weights or Coefficients of independent variables in the Linear regression model --> Model Pa-rameter II. K in the K-Nearest Neighbour algorithm --> Model Hyperparameter III. Learning rate for training a neural network --> Model Hyperparameter IV. Batch Size --> Model Parameter

Question23: All aggregate functions except _____ ignore null values in their input collection

Question24: In a simple linear regression model (One independent variable), If we change the input variable by 1 unit. How much output variable will change?

Question25: Consider a data frame df with columns ['A', 'B', 'C', 'D'] and rows ['r1', 'r2', 'r3']. What does the ex-pression df[lambda x : x.index.str.endswith('3')] do?

Question26: Which is the visual depiction of data through the use of graphs, plots, and informational graphics?

Question27: You previously trained a model using a training dataset. You want to detect any data drift in the new data collected since the model was trained.
What should you do?

Question28: Which one is not the types of Feature Engineering Transformation?

Question29: Mark the incorrect statement regarding Python UDF?

Question30: Performance metrics are a part of every machine learning pipeline, Which ones are not the performance metrics used in the Machine learning?