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Axtria Senior Associate Interview Questions and Answers

Updated 12 Jun 2024

Q1. Random forest vs decision tree vs xg boost

Ans.

Random forest is an ensemble method using multiple decision trees, XGBoost is a gradient boosting algorithm that builds trees sequentially.

  • Random forest is an ensemble learning method that builds multiple decision trees and combines their predictions.

  • Decision tree is a single tree model that makes decisions based on features to predict outcomes.

  • XGBoost is a gradient boosting algorithm that builds trees sequentially, optimizing the model's performance.

  • Random forest reduces ove...read more

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Q2. Difference between Delete and Truncate in SQL

Ans.

Delete removes specific rows from a table, while Truncate removes all rows from a table.

  • Delete is a DML command, while Truncate is a DDL command.

  • Delete can be rolled back, while Truncate cannot be rolled back.

  • Delete maintains the table structure and indexes, while Truncate resets the table structure and indexes.

  • Delete triggers delete triggers and delete constraints, while Truncate does not trigger any triggers or constraints.

  • Delete is slower than Truncate for large tables.

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Q3. Code any program in 2 languages

Ans.

I can code a program in Python and Java.

  • I am proficient in both Python and Java programming languages.

  • I have experience in developing web applications using Python and Java frameworks.

  • I can write efficient and optimized code in both languages.

  • I can develop programs for data analysis, machine learning, and automation using Python.

  • I can develop enterprise-level applications using Java.

  • Examples: Python - a program to scrape data from a website, Java - a program to implement a so...read more

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Q4. Culture about Axtria and policies

Ans.

Axtria promotes a collaborative and inclusive culture with a focus on innovation and growth.

  • Axtria values diversity and inclusion in the workplace

  • The company encourages innovation and creativity

  • There are policies in place to support employee growth and development

  • Axtria promotes a collaborative work environment

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Q5. Ridge and lasso regression difference

Ans.

Ridge and lasso regression are both regularization techniques used in linear regression to prevent overfitting by adding penalty terms to the cost function.

  • Ridge regression adds a penalty term equivalent to the square of the magnitude of coefficients, while lasso regression adds a penalty term equivalent to the absolute value of the magnitude of coefficients.

  • Ridge regression tends to shrink the coefficients towards zero but does not eliminate them completely, while lasso regr...read more

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Q6. Assumptions of regression

Ans.

Assumptions of regression

  • Linearity: The relationship between the independent and dependent variables is linear.

  • Independence: The residuals are independent of each other.

  • Homoscedasticity: The variance of the residuals is constant across all levels of the independent variables.

  • Normality: The residuals are normally distributed.

  • No multicollinearity: The independent variables are not highly correlated with each other.

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Interview Process at Axtria Senior Associate

based on 11 interviews
2 Interview rounds
Aptitude Test Round
One-on-one Round
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