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I applied via Referral and was interviewed in May 2024. There were 2 interview rounds.
Hadoop architecture is a distributed computing framework for processing large data sets across clusters of computers.
Hadoop consists of HDFS (Hadoop Distributed File System) for storage and MapReduce for processing.
HDFS divides data into blocks and stores them across multiple nodes in a cluster.
MapReduce is a programming model for processing large data sets in parallel across a distributed cluster.
Hadoop also includes ...
Hadoop is a distributed storage system while Spark is a distributed processing engine.
Hadoop is primarily used for storing and processing large volumes of data in a distributed environment.
Spark is designed for fast data processing and can perform in-memory computations, making it faster than Hadoop for certain tasks.
Hadoop uses MapReduce for processing data, while Spark uses Resilient Distributed Datasets (RDDs) for f...
Barclays Shared Services interview questions for popular designations
I was interviewed in Mar 2024.
Maths and general knowledge
Environmental studies
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I applied via Job Portal and was interviewed in Sep 2023. There was 1 interview round.
Credit risk is the risk of loss due to a borrower's failure to repay a loan or meet contractual obligations.
Credit risk is the risk that a borrower will default on a loan or debt obligation.
It is the potential loss that a lender may suffer if a borrower fails to make payments.
Factors that contribute to credit risk include the borrower's credit history, financial stability, and economic conditions.
Lenders use credit sco...
I applied via Referral and was interviewed before Aug 2023. There were 2 interview rounds.
Regression is a statistical method to predict continuous outcomes, while classification is used to predict categorical outcomes.
Regression is used when the target variable is continuous, such as predicting house prices based on features like size and location.
Classification is used when the target variable is categorical, like predicting whether an email is spam or not based on its content.
Regression models include lin...
Hyper parameters are settings that are set before the learning process begins and affect the learning process itself.
Hyper parameters are not learned during the training process, but are set before training begins.
They control the learning process and impact the performance of the model.
Examples include learning rate, number of hidden layers, and batch size in neural networks.
Improving model efficiency involves feature selection, hyperparameter tuning, and ensemble methods.
Perform feature selection to reduce dimensionality and focus on relevant features
Optimize hyperparameters using techniques like grid search or random search
Utilize ensemble methods like bagging or boosting to improve model performance
Consider using more advanced algorithms like deep learning for complex data patterns
I applied via LinkedIn and was interviewed in May 2022. There were 2 interview rounds.
Unix commands for permissions
chmod - change file mode bits
chown - change file owner and group
ls - list directory contents with permissions
umask - set default file permissions
I applied via Recruitment Consulltant and was interviewed before Oct 2021. There were 3 interview rounds.
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