1. ML Design on how to build a chat bot for a BookMyShow Platform? 2. Resume questions revolved around name entity recognition like - what are the metrices used. - how did you solve entity disambiguation. - What was the evaluation criterian. - how was training data created.
Machine Learning concepts. Statistics etc
What features can be used for a credit risk model
Questions around product and metrics: LTV, forecasting, and A/B testing.
Behavioral questions / technical questions on Machine Learning and statistics
SQL: Nested queries Python: Pandas aggregations & pivots ML: Describe multicollinearity and how to deal with it Statistics & Experimentation: How would you assess the effects of email reminders on reducing average medical costs of high risk members?
1. Explain OLS 2. How to build linear regression 3. Explain modeling process
p value
confidence interval
python data type
Viewing 771 - 780 interview questions