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In a time interval of 15-minutes, the probability that you may see a shooting star or a bunch of them is 0.2. What is the percentage chance of you seeing at least one star shooting from the sky if you are under it for about an hour? Suppose you have a medical test for a rare disease that is 99% accurate. If the disease occurs in 1% of the population, what is the probability that someone who tests positive actually has the disease?
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Senior Data Scientist

Interviewed at Microsoft

4★
May 1, 2024

In a time interval of 15-minutes, the probability that you may see a shooting star or a bunch of them is 0.2. What is the percentage chance of you seeing at least one star shooting from the sky if you are under it for about an hour? Suppose you have a medical test for a rare disease that is 99% accurate. If the disease occurs in 1% of the population, what is the probability that someone who tests positive actually has the disease?

Round 1 Coding. 1. Perfect squares 2. Binary tree traversal Round 2: ML Basics 1. Stats question, with Bayes theorem 2. AB testing 3. GBM, boosting vs bagging 4. Chi square test Round 3: NLP skills Walk then through one of your projects. Chatbotb design Round 4: bar raiser Beginning from your first company, you need to tell them how you fit in to their values. They ask how well you performed, why not promoted etc. Each one they ask which was the most challenging work and why? Round 5: team fit for 30 mins A young kid from business gives you an overview of the team and work then gives you a scenario on how can you set up guard rails in a chatbot system. Go into one of your projects, see how you talk through it, questions you asked etc. I never got to know why i got rejected but i think i talked about a half baked idea from my previous project which didn't look pleasing business wise. Anyway there were plenty things that went right in the last one so no idea what happened
avatar

Senior Data Scientist

Interviewed at Revolut

4★
Dec 5, 2024

Round 1 Coding. 1. Perfect squares 2. Binary tree traversal Round 2: ML Basics 1. Stats question, with Bayes theorem 2. AB testing 3. GBM, boosting vs bagging 4. Chi square test Round 3: NLP skills Walk then through one of your projects. Chatbotb design Round 4: bar raiser Beginning from your first company, you need to tell them how you fit in to their values. They ask how well you performed, why not promoted etc. Each one they ask which was the most challenging work and why? Round 5: team fit for 30 mins A young kid from business gives you an overview of the team and work then gives you a scenario on how can you set up guard rails in a chatbot system. Go into one of your projects, see how you talk through it, questions you asked etc. I never got to know why i got rejected but i think i talked about a half baked idea from my previous project which didn't look pleasing business wise. Anyway there were plenty things that went right in the last one so no idea what happened

difference between regression and classification then what is difference between linear and logistic if logitistic regression is classifying why is it called regression evaluation metrics for linear regression. difference between rsquare and adjusted rsquare? what if an irrelevant feature is kept will it increase rquare or will it stay the same? what does rsquare tells you? how does rsquare works or how does it behaves? if the rsquare is 0.8 what does it mean? what are we interpreting from 0.8 which of the l1 and l2 is direction based? what are the advantages and disdadvantages of kmeans clustering? what are the methods to determine optimum k? what does silhouette score mean how it works? why it is called elbow method? how are you going to pass categorical feature to kmeans clustering? if you have 100 features are you going to pass it directly or what will you do? consider two tables a and b, table a has 10 rows, table b has 20 rows. both have ID column to match on. If I do the inner join what is the minimum and maximum number of rows that we will get? select 3 from employee - what will this print [{}({)}] how to balance the brackets using python? what in this case - [{}()]?
avatar

Senior Data Scientist

Interviewed at Tredence

3.9★
Oct 8, 2024

difference between regression and classification then what is difference between linear and logistic if logitistic regression is classifying why is it called regression evaluation metrics for linear regression. difference between rsquare and adjusted rsquare? what if an irrelevant feature is kept will it increase rquare or will it stay the same? what does rsquare tells you? how does rsquare works or how does it behaves? if the rsquare is 0.8 what does it mean? what are we interpreting from 0.8 which of the l1 and l2 is direction based? what are the advantages and disdadvantages of kmeans clustering? what are the methods to determine optimum k? what does silhouette score mean how it works? why it is called elbow method? how are you going to pass categorical feature to kmeans clustering? if you have 100 features are you going to pass it directly or what will you do? consider two tables a and b, table a has 10 rows, table b has 20 rows. both have ID column to match on. If I do the inner join what is the minimum and maximum number of rows that we will get? select 3 from employee - what will this print [{}({)}] how to balance the brackets using python? what in this case - [{}()]?

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