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I applied via Referral and was interviewed in Apr 2023. There were 3 interview rounds.
Data science, ML concepts, statistics, python output
Correlation measures the strength and direction of a relationship between two variables. A correlation of 0 indicates no linear relationship.
Correlation measures the degree to which two variables move in relation to each other. It ranges from -1 to 1.
A correlation of 0 means there is no linear relationship between the variables. They are not related in a linear fashion.
For example, if the correlation between hours of s...
Regression models can be evaluated using R squared and adjusted R squared to measure the goodness of fit.
R squared measures the proportion of the variance in the dependent variable that is predictable from the independent variables.
Adjusted R squared adjusts for the number of predictors in the model, providing a more accurate measure of goodness of fit.
R squared can be artificially inflated by adding more predictors, w...
Regularization techniques help prevent overfitting in machine learning models. Ridge regression adds L2 regularization, while Lasso regression adds L1 regularization.
Regularization techniques help prevent overfitting by adding a penalty term to the loss function.
Ridge regression adds the squared magnitude of coefficients as penalty term (L2 regularization).
Lasso regression adds the absolute magnitude of coefficients as...
Decision trees are a popular machine learning algorithm used for classification and regression tasks.
Decision trees are a flowchart-like structure where each internal node represents a feature or attribute, each branch represents a decision rule, and each leaf node represents the outcome.
To select parent and child nodes, the algorithm calculates the best split at each node based on criteria like Gini impurity or inform...
Explanation of bagging, boosting, ensemble models, handling overfitting, and precision-recall-ROC curve.
Bagging (Bootstrap Aggregating) involves training multiple models on different subsets of the training data and combining their predictions through averaging or voting.
Boosting involves training multiple models sequentially, with each model correcting the errors of its predecessor.
Ensemble models combine multiple ind...
Creating dictionary in Python from 2 lists, using window functions and joins in SQL
To create a dictionary in Python from 2 lists and key values, you can use the zip() function
Example: dict(zip(keys_list, values_list))
For SQL window functions like Rank(), you can use the OVER() clause
Example: SELECT column1, column2, RANK() OVER(ORDER BY column3) AS rank_column FROM table_name
For SQL joins, you can use INNER JOIN, LEFT ...
posted on 5 May 2022
I applied via LinkedIn and was interviewed in Nov 2021. There were 3 interview rounds.
Be confident
I applied via Campus Placement and was interviewed before May 2023. There were 2 interview rounds.
Medium to hard level questions were asked and that mostly covers basics of DSA
posted on 23 Dec 2024
posted on 7 May 2017
I appeared for an interview in Jun 2016.
I applied via Other and was interviewed in Nov 2019. There were 5 interview rounds.
I appeared for an interview in Nov 2020.
I applied via Naukri.com and was interviewed in May 2021. There were 5 interview rounds.
I applied via Naukri.com
Were very hard questions and all were related to basic arithmetic and analytics and statistics.
Some of the top questions asked at the Air India ml engineer interview -
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