1. Python Coding - Pandas, List Operations, DSA 2. Statistics & Probability - CLT, Bayesian, Conditional, etc. 3. ML Questions - Logistics Regression, Evaluation Metrics, Decision Trees, Optimisation 4. Analytics & Probability Puzzles 5. How do you deal with difficult ppl in teams, etc.
How have you managed high achievers vs low performers in your team?
Basics of statistics and machine learning
Tell us about your experience.
Describe your experience in the data science field.
Q: Problem solving Q: Architecture design for impersonation classifier Q: Challenges in past projects, both technical and non-technical
Soft Skills questions in HR part and general data science discussion in Technical part
What is regularization? What is a linear model?
Give me an example project that you worked on.
What is CI/CD pipeline and what is customer segmentation?
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