Data Science III

Welcome to your quiz on Data Science III. All the best!

 

How can you assess a good logistic model?
What are various steps involved in a typical Analytics / Data Science project?
During analysis, how do you treat missing values?
What is Machine Learning?
You created a predictive model of a quantitative outcome variable using multiple regressions. What are the steps you would follow to validate the model?
What is regularization and what is it used for? 
Why L1 regularizations causes parameter sparsity whereas L2 regularization does not?



 

 

 

 

 

 

 

 

 
How can you deal with different types of seasonality in time series modeling?
Can you cite some examples where a false positive is important than a false negative?



 

 

 

 

 

 

 

 

 

 
Can you cite some examples where a false negative important than a false positive?

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