Linear Regression Assumptions, Boosting and Bagging. Regularisation, Feature Selection Methods, Forecasting
Science Interview Questions
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Price optimization
Explain the difference between type 1 and type 2 error.
Go through resume and many case study.
Given a dataset which we cannot even see properly on hackerrank, build 2 ML models and answer insight related questions within 2 hours. It made no sense. The dataset was in raw form, had to be studied and converted into features and target, split for training/testing and report accuracy. This is not how a data science task can be completed.
Make sure to study recommendation engines, since this is the bread and butter of their work. They don't really have any interest in your work experience, like many tech interviews.
Lots of coding questions and data analysis tasks.
¿En que año de la facultad estas cursando actualmente?
Why do you interest in Flipkart?
Given the word, "pepper," what are the number of ways to create words (valid or not) using the letters in this word?
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