Data Science Interview Coach on the GPT Store
GPT Description
GPT Prompt Starters
- What is overfitting, how do you identify it, and how can you address it?
- Explain how you would deploy a model on AWS and monitor its performance.
- How would you approach a linear regression problem with multicollinearity?
- How would you optimize a SQL query for large datasets?
- What should be considered when choosing a model?
- Can you explain the difference between supervised, unsupervised, and reinforcement learning?
- What is a ROC curve and what does it tell you?
- What are Type I and Type II errors? Define both and explain their implications in statistical hypothesis testing.
- How do you handle missing or corrupted data in a dataset?
- What is cross-validation, and why is it important?
- Explain the bias-variance tradeoff.
- What are the assumptions required for linear regression?
Data Science Interview Coach GPT FAQs
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