Flipkart Data Scientist Interview Questions and Answers

Business Related case study, signed NDA

Q1. Count number of Parameters in BERT
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Q2. 3 sum array problem
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Q1. Explain bagging vs boosting
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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

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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