What are the metrics you will use to track if Uber's paid advertising strategies to acquire customers work? How will you figure out the acceptable cost of customer acquisition?
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Why is Python used in data science?
A box has 12 red cards and 12 black cards. Another box has 24 red cards and 24 black cards. You want to draw two cards at random from one of the two boxes, which box has a higher probability of getting cards of same colour and why?
Can you cite some examples where both false positive and false negatives are equally important?
Can you define feature vector?
What are an eigenvalue and eigenvector?
What does the future hold for data scientists?
Do we have different selection biases, if yes, what are they?
How can you compute an inverse matrix faster by playing with some computation tricks?
Can you explain data cleansing?
What are independent graphics subsystems?
What exactly does a data scientist do?
What is cart and chaid?