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FlyNava Technologies
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I applied via campus placement at Sastra University and was interviewed in Sep 2024. There was 1 interview round.
The coding test was a Hackerrank contest where we had to solve 2 coding problems within 60 minutes.
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A pivot table in Excel is a data summarization tool that allows you to reorganize and summarize selected columns and rows of data.
Allows users to summarize and analyze large datasets
Can easily reorganize data by dragging and dropping fields
Provides options to calculate sums, averages, counts, etc. for data
Helps in creating interactive reports and charts
Useful for identifying trends and patterns in data
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...
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...
A pivot table in Excel is a data summarization tool that allows you to reorganize and summarize selected columns and rows of data.
Allows users to summarize and analyze large datasets
Can easily reorganize data by dragging and dropping fields
Provides options to calculate sums, averages, counts, etc. for data
Helps in creating interactive reports and charts
Useful for identifying trends and patterns in data
Forecasting problem - Predict daily sku level sales
Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.
Bias is the error introduced by approximating a real-world problem, leading to underfitting.
Variance is the error introduced by modeling the noise in the training data, leading to overfitting.
High bias can cause a model to miss relevant relationships between features and target variable.
High variance can cause a model to ...
Parametric models make strong assumptions about the form of the underlying data distribution, while non-parametric models do not.
Parametric models have a fixed number of parameters, while non-parametric models have a flexible number of parameters.
Parametric models are simpler and easier to interpret, while non-parametric models are more flexible and can capture complex patterns in data.
Examples of parametric models inc...
I applied via Company Website and was interviewed in Mar 2024. There were 2 interview rounds.
Python, Pyspark, Scala, Kafka
based on 1 interview
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