Explain while working on a data set, how do you select important variables?
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How will you test a machine learning model for accuracy?
Name some packages in r and python for building regression models.
A test has a true positive rate of 100% and false positive rate of 5%. There is a population with a 1/1000 rate of having the condition the test identifies. Considering a positive test, what is the probability of having that condition?
Explain k-mean?
What do you understand by ensemble learning?
How would churn help predict and control churn for a customer?
Explain how to merge the files into a single dataframe?
How is data science different from data analytics?
What is overfitting?
Which technique is used to predict categorical responses?
Which one you prefer R or Python for text analytics?
How can I become a data scientist?
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