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I applied via Company Website and was interviewed before Feb 2023. There was 1 interview round.
I applied via Naukri.com and was interviewed in Jan 2021. There were 4 interview rounds.
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I applied via Walk-in and was interviewed before Aug 2021. There were 2 interview rounds.
Transposing a data set involves flipping rows and columns.
Identify the data set to be transposed
Create a new table with the columns and rows flipped
Copy the data from the original table to the new table
Transpose can be done using Excel, Python, R, SQL, etc.
Example: Transposing a table of sales data to have products as rows and months as columns
I applied via Walk-in and was interviewed before Apr 2021. There were 2 interview rounds.
I applied via Job Portal and was interviewed before Jan 2021. There were 2 interview rounds.
I applied via Naukri.com and was interviewed in Jun 2021. There was 1 interview round.
C is a procedural language while Java is an object-oriented language.
C is compiled while Java is interpreted
C has pointers while Java does not
Java has automatic garbage collection while C does not
Java is platform-independent while C is not
Java has built-in support for multithreading while C does not
I applied via Company Website and was interviewed before Jul 2022. There were 5 interview rounds.
I applied via LinkedIn and was interviewed in Oct 2023. There were 2 interview rounds.
Normal questions on statistics and python graph and charts guesstimated
I have worked on various projects involving data analysis, visualization, and interpretation.
Developed predictive models using machine learning algorithms
Performed data cleaning and preprocessing to improve data quality
Created interactive dashboards for data visualization
Conducted statistical analysis to identify trends and patterns
Collaborated with cross-functional teams to derive actionable insights
I typically utilize tuning parameters such as learning rate, regularization strength, batch size, and number of epochs.
Learning rate: Adjusting the step size during optimization to control how quickly the model learns.
Regularization strength: Balancing between fitting the training data well and preventing overfitting.
Batch size: Determining the number of samples processed before updating the model.
Number of epochs: Set...
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