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I applied via Referral and was interviewed before May 2022. There were 4 interview rounds.
Typing Skills - Speed and Accuracy
Question on internal working of hashmap, multi-threading, DSA, and coding.
HashMap is a data structure that stores key-value pairs and uses hashing to retrieve values quickly.
Multi-threading is the ability of a CPU to execute multiple threads concurrently.
DSA stands for Data Structures and Algorithms, which are fundamental concepts in computer science.
Coding involves writing instructions in a programming language to cre
I applied via Naukri.com and was interviewed in Jun 2024. There were 3 interview rounds.
To find the second maximum number in a list, sort the list in descending order and return the second element.
Sort the list in descending order
Return the second element in the sorted list
Loops in Informatica are used to iterate over a set of data or perform repetitive tasks.
Loops in Informatica can be implemented using the 'Expression' or 'Router' transformations.
They are useful for processing multiple rows of data in a mapping.
Common types of loops include 'While' and 'For' loops.
Loops can help in performing complex data transformations and validations.
Two coding round in Javascript, first one to right CRUD operation in React.
Second one have to right JS for Flattened Array
Some mcq questions and coding question. Both where easy to medium level. Prepare combination/permutation/Time complexity etc
A question related to Binary search and some other follow ups.
I applied via Naukri.com and was interviewed before Oct 2022. There were 4 interview rounds.
They asked basic java programs
Adding 2 no by using strams.
I applied via Campus Placement and was interviewed before Sep 2023. There was 1 interview round.
Random forest is an ensemble learning method that builds multiple decision trees and merges them to improve accuracy and prevent overfitting.
Random forest is a type of ensemble learning method.
It builds multiple decision trees during training.
Each tree is built using a subset of the training data and a random subset of features.
The final prediction is made by averaging the predictions of all the individual trees.
Random...
Boosting is a machine learning ensemble technique where multiple weak learners are combined to create a strong learner.
Boosting is an iterative process where each weak learner is trained based on the errors of the previous learners.
Examples of boosting algorithms include AdaBoost, Gradient Boosting, and XGBoost.
Boosting is used to improve the accuracy of models and reduce bias and variance.
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