Filter interviews by
I applied via Naukri.com and was interviewed before Jan 2024. There was 1 interview round.
I am a data scientist with a background in statistics and machine learning.
Background in statistics and machine learning
Experience with data analysis and visualization tools like Python, R, and Tableau
Strong problem-solving skills
Ability to communicate complex technical concepts to non-technical stakeholders
Developed a predictive model for customer churn in a telecom company using machine learning algorithms.
Used Python for data preprocessing and model building
Implemented algorithms like Random Forest and Logistic Regression
Evaluated model performance using metrics like accuracy and AUC-ROC curve
Top trending discussions
I applied via Referral and was interviewed before Sep 2021. There was 1 interview round.
I applied via Job Fair and was interviewed in Jun 2022. There were 3 interview rounds.
Hospitality management
I applied via Walk-in and was interviewed in Nov 2021. There were 2 interview rounds.
I applied via Recruitment Consulltant and was interviewed before Mar 2022. There were 2 interview rounds.
All.ptp question are there. There are 25 que are there and 4 option for one que
I applied via LinkedIn and was interviewed in Sep 2020. There were 5 interview rounds.
VIF stands for Variance Inflation Factor, a measure of multicollinearity in regression analysis.
VIF is used to detect the presence of multicollinearity in regression analysis.
It measures how much the variance of the estimated regression coefficient is increased due to multicollinearity.
A VIF value of 1 indicates no multicollinearity, while a value greater than 1 suggests increasing levels of multicollinearity.
A commonl...
I applied via Walk-in and was interviewed in Mar 2020. There was 1 interview round.
R square is a statistical measure that represents the proportion of the variance in the dependent variable explained by the independent variables.
R square is a value between 0 and 1, where 0 indicates that the independent variables do not explain any of the variance in the dependent variable, and 1 indicates that they explain all of it.
It is used to evaluate the goodness of fit of a regression model.
Adjusted R square t...
Variable reducing techniques are methods used to identify and select the most relevant variables in a dataset.
Variable reducing techniques help in reducing the number of variables in a dataset.
These techniques aim to identify the most important variables that contribute significantly to the outcome.
Some common variable reducing techniques include feature selection, dimensionality reduction, and correlation analysis.
Fea...
The Wald test is used in logistic regression to check the significance of the variable.
The Wald test calculates the ratio of the estimated coefficient to its standard error.
It follows a chi-square distribution with one degree of freedom.
A small p-value indicates that the variable is significant.
For example, in Python, the statsmodels library provides the Wald test in the summary of a logistic regression model.
Multicollinearity in logistic regression can be checked using correlation matrix and variance inflation factor (VIF).
Calculate the correlation matrix of the independent variables and check for high correlation coefficients.
Calculate the VIF for each independent variable and check for values greater than 5 or 10.
Consider removing one of the highly correlated variables or variables with high VIF to address multicollinear...
Bagging and boosting are ensemble methods used in machine learning to improve model performance.
Bagging involves training multiple models on different subsets of the training data and then combining their predictions through averaging or voting.
Boosting involves iteratively training models on the same dataset, with each subsequent model focusing on the samples that were misclassified by the previous model.
Bagging reduc...
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 a type of regression analysis used for predicting the outcome of a categorical dependent variable based on one or more predictor variables.
It uses a logistic function to model the probability of the dependent variable taking a particular value.
It is commo...
Gini coefficient measures the inequality among values of a frequency distribution.
Gini coefficient ranges from 0 to 1, where 0 represents perfect equality and 1 represents perfect inequality.
It is commonly used to measure income inequality in a population.
A Gini coefficient of 0.4 or higher is considered to be a high level of inequality.
Gini coefficient can be calculated using the Lorenz curve, which plots the cumulati...
A chair is a piece of furniture used for sitting, while a cart is a vehicle used for transporting goods.
A chair typically has a backrest and armrests, while a cart does not.
A chair is designed for one person to sit on, while a cart can carry multiple items or people.
A chair is usually stationary, while a cart is mobile and can be pushed or pulled.
A chair is commonly found in homes, offices, and public spaces, while a c...
Outliers can be detected using statistical methods like box plots, z-score, and IQR. Treatment can be removal or transformation.
Use box plots to visualize outliers
Calculate z-score and remove data points with z-score greater than 3
Calculate IQR and remove data points outside 1.5*IQR
Transform data using log or square root to reduce the impact of outliers
I applied via Campus Placement and was interviewed in Dec 2020. There were 3 interview rounds.
Accuracy is the closeness of a measured value to the true value. Precision is the consistency of repeated measurements.
Accuracy measures how close a measurement is to the true value
Precision measures the consistency of repeated measurements
Accuracy can be affected by systematic errors
Precision can be affected by random errors
Accuracy and precision are both important in scientific measurements
based on 2 interviews
Interview experience
based on 2 reviews
Rating in categories
Assistant Manager
370
salaries
| ₹5 L/yr - ₹19 L/yr |
Manager
232
salaries
| ₹9 L/yr - ₹35 L/yr |
Senior Manager
166
salaries
| ₹9.2 L/yr - ₹36.2 L/yr |
Deputy Manager
143
salaries
| ₹6.1 L/yr - ₹23 L/yr |
Sales Manager
118
salaries
| ₹2 L/yr - ₹9 L/yr |
UltraTech Cement
JK Cement
Grasim Industries
ACC