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Which one is not the feature engineering techniques used in ML data science world?
Which one is not the feature engineering techniques used in ML data science world?A . ImputationB . BinningC . One hot encodingD . StatisticalView AnswerAnswer: D Explanation: Feature engineering is the pre-processing step of machine learning, which is used to transform raw data into features that can be used for...
Skewness of Normal distribution is ___________
Skewness of Normal distribution is ___________A . NegativeB . PositiveC . 0D . UndefinedView AnswerAnswer: C Explanation: Since the normal curve is symmetric about its mean, its skewness is zero. This is a theoretical explanation for mathematical proofs, you can refer to books or websites that speak on the same...
What Can Snowflake Data Scientist do in the Snowflake Marketplace as Consumer?
What Can Snowflake Data Scientist do in the Snowflake Marketplace as Consumer?A . Discover and test third-party data sources.B . Receive frictionless access to raw data products from vendors.C . Combine new datasets with your existing data in Snowflake to derive new business in-sights.D . Use the business intelligence (BI)/ML/Deep...
As Data Scientist looking out to use Reader account, Which ones are the correct considerations about Reader Accounts for Third-Party Access?
As Data Scientist looking out to use Reader account, Which ones are the correct considerations about Reader Accounts for Third-Party Access? A. Reader accounts (formerly known as “read-only accounts”) provide a quick, easy, and cost-effective way to share data without requiring the consumer to become a Snowflake customer. B. Each...
Which one is not the feature engineering techniques used in ML data science world?
Which one is not the feature engineering techniques used in ML data science world?A . ImputationB . BinningC . One hot encodingD . StatisticalView AnswerAnswer: D Explanation: Feature engineering is the pre-processing step of machine learning, which is used to transform raw data into features that can be used for...
Which one is not the feature engineering techniques used in ML data science world?
Which one is not the feature engineering techniques used in ML data science world?A . ImputationB . BinningC . One hot encodingD . StatisticalView AnswerAnswer: D Explanation: Feature engineering is the pre-processing step of machine learning, which is used to transform raw data into features that can be used for...
As Data Scientist looking out to use Reader account, Which ones are the correct considerations about Reader Accounts for Third-Party Access?
As Data Scientist looking out to use Reader account, Which ones are the correct considerations about Reader Accounts for Third-Party Access? A. Reader accounts (formerly known as “read-only accounts”) provide a quick, easy, and cost-effective way to share data without requiring the consumer to become a Snowflake customer. B. Each...
As Data Scientist looking out to use Reader account, Which ones are the correct considerations about Reader Accounts for Third-Party Access?
As Data Scientist looking out to use Reader account, Which ones are the correct considerations about Reader Accounts for Third-Party Access? A. Reader accounts (formerly known as “read-only accounts”) provide a quick, easy, and cost-effective way to share data without requiring the consumer to become a Snowflake customer. B. Each...
Which are the following additional Metadata columns Stream contains that could be used for creating Efficient Data science Pipelines & helps in transforming only the New/Modified data only?
Which are the following additional Metadata columns Stream contains that could be used for creating Efficient Data science Pipelines & helps in transforming only the New/Modified data only?A . METADATA$ACTIONB . METADATA$FILE_IDC . METADATA$ISUPDATED . METADATA$DELETEE . METADATA$ROW_IDView AnswerAnswer: A, C, E Explanation: A stream stores an offset for the...
Which ones are the key actions in the data collection phase of Machine learning included?
Which ones are the key actions in the data collection phase of Machine learning included? A. Label B. Ingest and Aggregate C. Probability D. MeasureView AnswerAnswer: A, B, D Explanation: In the context of the data collection phase of machine learning, the key actions would be: A. Label - This...
