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I applied via Naukri.com and was interviewed before Aug 2022. There were 3 interview rounds.
There some logical question and those are very interesting.
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ETL stands for Extract, Transform, Load. It is a process used in data warehousing to extract data from various sources, transform it into a consistent format, and load it into a target database.
ETL stands for Extract, Transform, Load
Extract: Involves extracting data from various sources such as databases, applications, and files
Transform: Involves cleaning, filtering, and transforming the extracted data into a consiste...
Data Coding, 1hr, series of questions in excel
I applied via Company Website and was interviewed before Mar 2022. There were 5 interview rounds.
Quantitative aptitude, reasoning with time limit
Excel tasks were given. There were total 2 tasks related to excel. 1st one was basic and second one was moderate level of difficulty. SQL queries were basic.
I applied via Walk-in and was interviewed in Aug 2022. There were 2 interview rounds.
I applied via Company Website and was interviewed in Aug 2021. There were 3 interview rounds.
Data entry is the process of entering data into a computer system or database.
It involves inputting data from various sources such as paper documents, electronic files, or audio recordings.
Accuracy and speed are important in data entry.
Common tasks include typing, scanning, and verifying data.
Examples of data entry jobs include transcribing medical records, inputting customer information, and updating inventory databas
Overfitting occurs when a machine learning model learns the training data too well, including noise and outliers, leading to poor generalization on new data.
Overfitting happens when a model is too complex and captures noise in the training data.
It leads to poor performance on unseen data as the model fails to generalize well.
Techniques to prevent overfitting include cross-validation, regularization, and early stopping.
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Overfitting occurs when a model learns the details and noise in the training data to the extent that it negatively impacts the model's performance on new data.
Overfitting happens when a model is too complex and captures noise in the training data.
It leads to poor generalization and high accuracy on training data but low accuracy on new data.
Techniques to prevent overfitting include cross-validation, regularization, and...
Code signal , SQL python questions
Take home coding assignment - 10 days analysis and recommendations
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