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Microsoft's 25 Data Science & AI Interview Questions - Acing the Data Science, AI Interview
- Microsoft AI School: Different Learning Paths
- AI Demos(Showcases the Data Presentation and Visualization): AI Demos
- Microsoft Azure AI Solutions (Similar to Amazon AWS): Projects
- Microsoft Research Podcast: Research Podcast (Courtesy: Petercooper via HackerNews)
- Merge k (in this case k=2) arrays and sort them.
- How best to select a representative sample of search queries from 5 million?
- Three friends in Seattle told you it's rainy. Each has a probability of 1/3 of lying. What's the probability of Seattle is rainy?
- Can you explain the fundamentals of Naive Bayes? How do you set the threshold?
- Can you explain what MapReduce is and how it works?
- Can you explain SVM?
- How do you detect if a new observation is an outlier? What is a bias-variance trade-off ?
- Discuss how to randomly select a sample from a product user population.
- How do you implement autocomplete?
- Describe the working of a gradient boost.
- Find the maximum of subsequence in an integer list.
- What would you do to summarize a twitter feed?
- Explain the steps for data wrangling and cleaning before applying machine learning algorithms.
- How to deal with unbalanced binary classification?
- How to measure distance between data point?
- Define variance.
- What is the difference between box plot and histogram?
- How do you solve the L2-regularized regression problem?
- How to compute an inverse matrix faster by playing around with some computational tricks?
- How to perform a series of calculations without a calculator. Explain the logic behind the steps.
- What is a difference between good and bad Data Visualization?
- How do you find percentile? Write the code for it.
- Find max sum subsequence from a sequence of values.
- What are the different regularization metrics L1 and L2?
- Create a function that checks if a word is a palindrome.