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IndusInd Bank Data Scientist Interview Questions and Answers
IndusInd Bank Data Scientist Interview Experiences
2 interviews found
Anonymous
(2 Questions)
- Q1. Logistic regression loss function
- Q2. Step function in ML context
- Ans.
Step function is a function that returns a constant value for a certain range of inputs.
In machine learning, step functions are used as activation functions in neural networks.
They are typically used in binary classification problems where the output is either 0 or 1.
Examples include Heaviside step function and sigmoid step function.
Skills evaluated in this interview
(1 Question)
- 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.
Skills evaluated in this interview
Data Scientist Jobs at IndusInd Bank
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Debanjali Ghosh
I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.
(3 Questions)
- Q1. Explain Sigmoid Function
- Ans.
Sigmoid function is a mathematical function that maps any real value to a value between 0 and 1.
Sigmoid function is commonly used in machine learning for binary classification problems.
It is defined as f(x) = 1 / (1 + e^(-x)), where e is the base of the natural logarithm.
The output of the sigmoid function is always in the range (0, 1).
It is used to convert a continuous input into a probability value.
Example: f(0) = 0.5
- Q2. What is a T-test in logistic regression
- Ans.
A T-test in logistic regression is used to determine the significance of individual predictor variables.
T-test in logistic regression is used to test the significance of individual coefficients of predictor variables.
It helps in determining whether a particular predictor variable has a significant impact on the outcome variable.
The null hypothesis in a T-test for logistic regression is that the coefficient of the predi...
- Q3. How to fit model to an unexplored market
- Ans.
To fit a model to an unexplored market, conduct thorough market research, gather relevant data, identify key variables, test different models, and continuously iterate and refine the model.
Conduct thorough market research to understand the dynamics of the unexplored market
Gather relevant data on customer behavior, market trends, competition, etc.
Identify key variables that may impact the market and model outcomes
Test d...
Interview Preparation Tips
- Logistic Regression
- Banking
Skills evaluated in this interview
Anukriti Jain
Find second max in list, cal moving avg of a df
(1 Question)
- 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...
Skills evaluated in this interview
Data Scientist Interview Questions & Answers
Jana Small Finance Bank
Kunal Saraswat
posted on 18 Feb 2024
I was interviewed in Jan 2024.
(1 Question)
- Q1. Machine learning questions
Project Discussion on Eye flue detection
Interview Preparation Tips
Himani Tokas
(1 Question)
- Q1. Focus was on SQL, projects done so far, Machine Learning and Stats
Find second max in list, cal moving avg of a df
(1 Question)
- 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...
Skills evaluated in this interview
Data Scientist Interview Questions & Answers
Jana Small Finance Bank
Kunal Saraswat
posted on 18 Feb 2024
I was interviewed in Jan 2024.
(1 Question)
- Q1. Machine learning questions
Project Discussion on Eye flue detection
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