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Create a program in a language of your choice to read a text file with various tweets. The output should be 2 text files-one that contains the list of all unique words among all tweets along with the count for repeated words and the second file should contain the medium number of unique words for all tweets.
368You can roll a dice three times. You will be given $X where X is the highest roll you get. You can choose to stop rolling at any time (example, if you roll a 6 on the first roll, you can stop). What is your expected pay-out?
328You are at a Casino. You have two dices to play with. You win $10 every time you roll a 5. If you play till you win and then stop, what is the expected pay-out?
359What 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?
Uber,
297How will you design the heatmap for Uber drivers to provide recommendation on where to wait for passengers? How would you approach this?
Uber,
1714Case Study based questions - Cars are implanted with speed tracker so that the insurance companies can track about our driving state. Based on this new scheme what kind of business questions can be answered?
457Which technique will you use to compare the performance of two back-end engines that generate automatic friend recommendations on Facebook?
447You have two tables-the first table has data about the users and their friends, the second table has data about the users and the pages they have liked. Write an SQL query to make recommendations using pages that your friends liked. The query result should not recommend the pages that have already been liked by a user.
411Post New Data Science Questions
Can you explain eigenvalue and eigenvector?
Can you define data discretization?
How do you use lambda in python?
Explain Examples of Data Science?
why is data cleaning important for analysis?
Which technique is used to predict categorical responses?
What are eigenvalue and eigenvector?
What do you understand by Ordinary Least Squares Linear Regression?
How are confidence intervals constructed and how will you interpret them?
What is the role of activation function?
Is macbook good for data science?
You own a clothing enterprise and want to improve your place in the market. How will you do it from the ground level ?
When do you need to update the algorithm in data science?
Can you cite some examples where both false positive and false negatives are equally important?
How do you handle missing values in python or r?
