i
IndusInd Bank
Filter interviews by
I applied via Naukri.com and was interviewed before Aug 2020. There were 3 interview rounds.
t-test is a statistical test used to determine if there is a significant difference between the means of two groups.
It compares the means of two groups and assesses if the difference is statistically significant.
It is commonly used in hypothesis testing and comparing the effectiveness of different treatments or interventions.
There are different types of t-tests, such as independent samples t-test and paired samples t-t...
A z-test is a statistical test used to determine whether two population means are significantly different from each other.
It is used when the sample size is large and the population standard deviation is known.
The test compares the sample mean to the population mean using the z-score formula.
The z-score is calculated as the difference between the sample mean and population mean divided by the standard deviation.
If the ...
Linear regression is a statistical method used to model the relationship between two variables.
It assumes a linear relationship between the dependent and independent variables.
It is used to predict the value of the dependent variable based on the value of the independent variable.
It can be used for both simple and multiple regression analysis.
Example: predicting the price of a house based on its size or predicting the ...
Logistic regression is a statistical method used to analyze and model the relationship between a binary dependent variable and one or more independent variables.
It is used to predict the probability of a binary outcome (0 or 1).
It is a type of regression analysis that uses a logistic function to model the relationship between the dependent and independent variables.
It is commonly used in machine learning and data analy...
The formula of logistic regression is a mathematical equation used to model the relationship between a binary dependent variable and one or more independent variables.
The formula is: log(odds) = β0 + β1x1 + β2x2 + ... + βnxn
The dependent variable is transformed using the logit function to obtain the log-odds ratio.
The independent variables are multiplied by their respective coefficients (β) and summed up with the inter...
Logistic regression is used for binary classification, while linear regression is used for predicting continuous values.
Logistic regression is a classification algorithm, while linear regression is a regression algorithm.
Logistic regression uses a logistic function to model the probability of the binary outcome.
Linear regression uses a linear function to model the relationship between the independent and dependent vari...
Model accuracy can be measured using metrics such as confusion matrix, ROC curve, and precision-recall curve.
Confusion matrix shows true positives, true negatives, false positives, and false negatives.
ROC curve plots true positive rate against false positive rate.
Precision-recall curve plots precision against recall.
Other metrics include accuracy, F1 score, and AUC-ROC.
Cross-validation can also be used to evaluate mode
AUC-ROC curve is a graphical representation of the performance of a classification model.
AUC-ROC stands for Area Under the Receiver Operating Characteristic curve.
It is used to evaluate the performance of binary classification models.
The curve plots the true positive rate (sensitivity) against the false positive rate (1-specificity) at various classification thresholds.
AUC-ROC ranges from 0 to 1, with a higher value in...
A random forest is an ensemble learning method that combines multiple decision trees to make predictions.
Random forest is a supervised learning algorithm.
It can be used for both classification and regression tasks.
It creates multiple decision trees and combines their predictions to make a final prediction.
Each decision tree is trained on a random subset of the training data and features.
Random forest reduces overfittin...
Random forest is an ensemble learning method that uses multiple decision trees to improve prediction accuracy.
Random forest builds multiple decision trees and combines their predictions to reduce overfitting.
Decision trees are prone to overfitting and can be unstable, while random forest is more robust.
Random forest can handle missing values and categorical variables better than decision trees.
Example: Random forest ca...
Top trending discussions
I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.
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
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...
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...
Find second max in list, cal moving avg of a df
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...
I applied via Job Portal and was interviewed in Aug 2023. There were 2 interview rounds.
Aptitude test for about an hour.
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
posted on 18 Feb 2024
I was interviewed in Jan 2024.
Project Discussion on Eye flue detection
I applied via campus placement at Indian Institute of Technology (IIT), Kharagpur and was interviewed in Dec 2022. There were 4 interview rounds.
Hard level aptitude questions... Time taking sums
based on 1 review
Rating in categories
Deputy Manager
3.7k
salaries
| ₹1.7 L/yr - ₹8.5 L/yr |
Assistant Manager
2.3k
salaries
| ₹1.5 L/yr - ₹6.3 L/yr |
Manager
1.8k
salaries
| ₹2.6 L/yr - ₹10.9 L/yr |
Service Delivery Manager
1.6k
salaries
| ₹1.9 L/yr - ₹6.3 L/yr |
Relationship Manager
1.6k
salaries
| ₹3 L/yr - ₹14 L/yr |
HDFC Bank
ICICI Bank
Axis Bank
Kotak Mahindra Bank