Karnataka Bank Data Scientist Interview Questions and Answers

Hard level aptitude questions... Time taking sums

Q1. Puzzles and probability questions
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Q2. Asking completely about data science projects in your resume
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Q1. Just asked some puzzle questions
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Q2. Asked if iam willing to relocate and about my family
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Aptitude test for about an hour.

Q1. Questions related to data science were asked based on your resume. Puzzles were asked too. Mostly they were from gfg.
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Q2. What are parameters used in a random forest.
Ans. 
Parameters used in a random forest include number of trees, maximum depth of trees, minimum samples split, and maximum features.
• Number of trees: The number of decision trees to be used in the random forest.

• Maximum depth of trees: The maximum depth allowed for each decision tree.

• Minimum samples split: The minimum number of samples required to split a node.

• Maximum features: The maximum number of features to consider when
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Q1. Explain about how recommendation engine work
Ans. 
Recommendation engines analyze user data to suggest items based on preferences and behavior.
• Recommendation engines use collaborative filtering to suggest items based on user behavior and preferences.

• They can also use content-based filtering to recommend items similar to ones the user has liked in the past.

• Some recommendation engines combine both collaborative and content-based filtering for more accurate suggestions.

• Ex...read more
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Find second max in list, cal moving avg of a df

Q1. What do you do if your model has higher false positives
Ans. 
Investigate the model performance metrics and adjust the threshold for classification.
• Analyze the confusion matrix to understand the distribution of false positives.

• Adjust the threshold for classification to reduce false positives.

• Consider using different evaluation metrics like precision, recall, and F1 score.

• Explore feature importance to identify variables contributing to false positives.
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Coding related objective questions

Q1. Basic questions based on cv. Questions based on python,SQL,ML algorithms
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Q1. Explain previous projects
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Q2. Explain 2 algo of your choice
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It was okay as the interview was scheduled on time.

Q1. They asked questions in the interview Including Python, Machine learning, SQL, Power BI
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