1. Explain the project End - End, from scratch to Model Building and selection? 2. Explain the Statistical Pre-Processing techniques you used in your project and explain each one of them. 3. Explain Confusion Matrix 4. Explain Type 1 and Type 2 Errors 5. How did you increase the ROI with your model.
Data Sciences Interview Questions
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Explain your resume projects and may ask you a question on pandas or numpy
What do you think about LLMs-as-a-judge
probability, distributions, normalization, models, coding
(R2) Discussion on linear regression, l1/l2 loss, overfitting, weight distribution.
- Past Experiences - How do you best fit well in the team
I've already mentioned in the process.
Q: Describe the color "white" to a blind person
Why are you interested in becoming a consultant.
Most surprising was probably the Powerpoint presentation. Did not see that one coming at all, and the timing is extremely stressful.
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