Python and SQL challenges via HackerRank Including: - How many edges does a fully connected (or complete) graph have? Multiple choice - What is the fundamental difference between k-means clustering and KNN? Multiple choice - Which command would be used to ensure any local tracked changes are also shared amongst remote repositories? Multiple choice - Given 2 fair 6-sided dice and a fair coin, what is the probability of rolling a combined score of 7 with the dice and having the coin show heads after tossing? Multiple choice - Given data matrix X of shape n x d and transformation matrix sigma of shape d x k, which matrix multiplications will produce a transformed data matrix Xdash of shape n x k? Multiple choice - The sigmoid function is defined. What does its value tend to as its input x moves towards negative infinity? Multiple choice - SQL challenge of 2 tables with example answer, typed answer in SQL language of choice required - You are playing a card game with three cards. Both sides of one card are black, both sides of another are white, and the remaining card has one black side and one white side. You pick a card at random and see it has a black side face-up. What is the probability that the other side of the card is white? Multiple choice - 'Descending Mount Trigonometry' question - code your own answer
Data Scientist Interview Questions
40,238 data scientist interview questions shared by candidates
You can look at the other interview reviews for the specific questions. Mine was very similar, although specific questions may differ.
Details on your CV (relevant projects) Basic probability and statistics Coding exercise in the programming language of your choice.
What’s the probability that in a room full of k people, at least 2 people will have the same birthday?
5 dices(6,6,6,20,30) what's the probability of the sum bigger than 36
One A/B test takehome challenge, one onsite data challenge and one day for cultural fit.
What assumptions would you make to underpin that answer?
What are some of the non-convex optimization methods?
generating a sorted vector from two sorted vectors.
How did you prevent overfitting when using Deep Learning models?
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