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Estimate the probability of a disease in a particular city given that the probability of the disease on a national level is low.
347How will you decide whether a customer will buy a product today or not given the income of the customer, location where the customer lives, profession and gender? Define a machine learning algorithm for this.
292From a long sorted list and a short 4 element sorted list, which algorithm will you use to search the long sorted list for 4 elements.
328How can you compare a neural network that has one layer, one input and output to a logistic regression model?
294You are about to get on a plane to Seattle, you want to know whether you have to bring an umbrella or not. You call three of your random friends and as each one of them if it's raining. The probability that your friend is telling the truth is 2/3 and the probability that they are playing a prank on you by lying is 1/3. If all 3 of them tell that it is raining, then what is the probability that it is actually raining in Seattle.
336You have been given the data on Facebook user's friending or defriending each other. How will you determine whether a given pair of Facebook users are friends or not?
366Post New Data Science Questions
Which package is used to do data import in r and python? How do you do data import in sas?
Where to seek help in case of discrepancies in tableau?
What are decorators in Python?
Write a program to segment a long string into a group of valid words using Dictionary. The result should return false if the string cannot be segmented. Also explain about the complexity of the devised solution.
How regularly must an algorithm be updated?
What is the difference between kmeans clustering and hierarchical clustering?
What is linear optimization? Where is it used?
What makes the difference between “long” and “wide” format data?
A certain couple tells you that they have two children, at least one of which is a girl. What is the probability that they have two girls?
How can you select k for k-means?
Explain the difference between sas, r and python programming?
Give an example of a data set that has a non-gaussian distribution?
Discuss decision tree algorithm?
How will you drop variables using indices in a data frame?
How much ram do I need for data science?
