IndusInd Bank Senior Data Scientist Interview Questions and Answers

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...read more

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 overf...read more

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...read more

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 ...read more

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 sample...read more

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 ...read more

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...read more

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 val...read more