Zepto Data Scientist Interview Questions and Answers

Q1. Came for campus. Asked questions around basics of ML namely CV, L1, L2 loss & their assumptions, Boosting and Bagging
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Q1. Gave a case study on solving a NLP problem
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Q1. Discussion on linear regression and regularisation techniques
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Q2. Discussion on tree based models and measures to score the models
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2 hours, 12th level math questions

1 hour, sql and python

Q1. Normal Data Science questions
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Q1. Salary discussion and HR related queries
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Q1. Explain bagging vs boosting
Ans. 
Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models.
• Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.

• Boosting involves training multiple models sequentially, where each subsequent model corrects the errors made by the previ...read more
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How to judge if the comment is actually describing a product

Practise 10 DSA medium and 10 hard questions on each topic.

Q1. Recursion problems are asked
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2 Question and live coding was conducted on self platform

Q1. Taking about ML and statitics
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