Credit Saison ml engineer Interview Questions and Answers

Q1. How to handle missing values in case of Kmeans cluster
Ans. 
Handle missing values in Kmeans cluster by imputing with mean, median, or mode.
• Impute missing values with mean, median, or mode of the feature

• Consider using algorithms like KNN imputation or MICE for more complex cases

• Drop rows or columns with missing values if they are insignificant in number

• Normalize data before imputing missing values to avoid bias
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Q2. How to handle imabalance in case of Naive Bayes
Ans. 
Handling imbalance in Naive Bayes involves using techniques like oversampling, undersampling, or using different evaluation metrics.
• Use oversampling techniques like SMOTE to create synthetic samples of the minority class.

• Use undersampling techniques to randomly remove samples from the majority class.

• Adjust class weights in the Naive Bayes algorithm to give more importance to the minority class.

• Use different evaluation ...read more
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3 questions easy-medium level leetcode problem I solved 2 completely and 3rd question partially (9/15 test cases passed) to move on to 2nd round

Q1. Implement an app similar to splitwise
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Q1. Stack based question Medium Difficulty DSA.
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Q2. Theory questions related Java, Spring, OOPs
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Q1. Medium-hard DSA question.
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Q2. Project related questions
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Q3. Design Patterns
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Q1. Company fit questions
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