Swiggy Data Scientist Interview Questions and Answers

Q1. Asked firstly some question over my resume then 2 case study type problems where i have to improve the recommdation system for zomato, and finally one coding question based on two pointer
Add your answer

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
Answered by AI
Add your answer

How to judge if the comment is actually describing a product

Business Related case study, signed NDA

Q1. Count number of Parameters in BERT
Add your answer
Q2. 3 sum array problem
Add your answer

Q1. Came for campus. Asked questions around basics of ML namely CV, L1, L2 loss & their assumptions, Boosting and Bagging
Add your answer

Q1. Gave a case study on solving a NLP problem
Add your answer

Explain dynamic programming with memoization

Q1. Where are you from, and why are you joining the company
Add your answer
Q2. Why are you joining the company
Add your answer

2 Question and live coding was conducted on self platform

Q1. Taking about ML and statitics
Add your answer

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

Q1. Recursion problems are asked
Add your answer

Q1. Normal Data Science questions
Add your answer

Q1. Salary discussion and HR related queries
Add your answer