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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.
302How 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.
261From 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.
298How can you compare a neural network that has one layer, one input and output to a logistic regression model?
260You 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.
292You 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?
312Post New Data Science Questions
Do we have different selection biases, if yes, what are they?
How will you prove that the square root of 2 is irrational?
Suppose that American Express has 1 million card members along with their transaction details. They also have 10,000 restaurants and 1000 food coupons. Suggest a method which can be used to pass the food coupons to users given that some users have already received the food coupons so far.
Develop an algorithm to sort two lists of sorted integers into a single list.
How can you compare a neural network that has one layer, one input and output to a logistic regression model?
In any 15-minute interval, there is a 20% probability that you will see at least one shooting star. What is the probability that you see at least one shooting star in the period of an hour?
Name some kinds of graphs and explain how you would build them in python or r.
Pick up a coin C1 given C1+C2 with probability of trials p (h1) =.7, p (h2) =.6 and doing 10 trials. And what is the probability that the given coin you picked is C1 given you have 7 heads and 3 tails?
What is the procedure to check the cumulative frequency distribution of any categorical variable?
Explain p-value?
What is logistic and linear regression? How do you treat multicollinearity and heteroscedasticity in regression?
What do you know about autoencoders?
Explain the difference between data science, machine learning and artificial intelligence?
Is it possible to capture the correlation between continuous and categorical variable?
what the aim of conducting a/b testing?
