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I applied via Internshala and was interviewed before Jun 2023. There was 1 interview round.
Yes, I have experience in PowerBI.
I have used PowerBI to create interactive visualizations and reports.
I have experience connecting PowerBI to various data sources such as SQL databases, Excel files, and APIs.
I have used DAX (Data Analysis Expressions) to create calculated columns and measures in PowerBI.
I have experience sharing and collaborating on PowerBI dashboards and reports with team members.
Join in SQL is used to combine rows from two or more tables based on a related column between them.
Join is used to retrieve data from multiple tables based on a related column
Types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN
Example: SELECT * FROM table1 INNER JOIN table2 ON table1.column = table2.column
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.
...
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...
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.
...
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...
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