Precision vs Recall, Type 1- type 2 error, assumptions of linear regression, why do we use big data, How use SVM for multiclass, how to deal with data imbalance, F statistic, F test, t test, Degree of freedom of linear regression model, Lasso vs ridge regression
Describe a situation where you worked as part of a team
1. How can you deploy a machine learning model? 2. Use cases of decision trees and matrix 3. The difference between R-square and adj R square
1. what is random forest? 2. given a dataset, what would be the output of the k-means algorithm? 3. what is a CNN? 4. why do you want to join walmart? 5. suppose you roll a die and earn whatever face you get. what is the expected return? 6. now suppose you have a chance to roll a second die. if you roll, you forfeit your earnings from the first round. when should you roll the second time?
1. OA 2. Data Challenge 3. All data science concepts. Probab, Stats, modelling
How you can filter out element from a list?
jkk 1. What is linear regression? Explain steps for modelling 2. What do you mean by R square and adjusted R square? 3. What is logistic regression? Explain steps for modelling 4. Forecasting methods like time series, ARIMA etc. 5. Basics of Tableau 6. Basic SQL queries 7. libraries of python and basic coding skills (hardly any questions related to this are asked) 8. Any analytics projects you have worked on or competitions you have participated in?
Which of the following proposition is true
probability, distributions, normalization, models, coding
tell me something about your self.
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