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I applied via Job Fair and was interviewed in Mar 2024. There was 1 interview round.
Hyper parameters are settings that control the learning process of a machine learning algorithm, such as the learning rate or regularization strength.
Hyper parameters for linear regression include learning rate, regularization strength, number of iterations, and batch size.
Learning rate controls the step size in updating the model parameters during training.
Regularization strength helps prevent overfitting by penalizin...
Gradient descent is an optimization algorithm used to minimize the cost function in machine learning by iteratively moving towards the minimum.
Gradient descent calculates the gradient of the cost function with respect to each parameter in the model.
It then updates the parameters in the opposite direction of the gradient to minimize the cost function.
The learning rate determines how big of a step to take in the directio...
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I applied via Walk-in and was interviewed before Apr 2020. There were 5 interview rounds.
I applied via Recruitment Consultant and was interviewed before Sep 2020. There were 3 interview rounds.
I applied via Campus Placement and was interviewed in Jul 2020. There was 1 interview round.
Java is platform independent due to its bytecode and JVM.
Java code is compiled into bytecode which is platform-independent.
JVM (Java Virtual Machine) interprets the bytecode and executes it on any platform.
JVM acts as an abstraction layer between the Java code and the underlying hardware.
This allows Java programs to run on any platform that has a JVM installed.
For example, a Java program written on a Windows machine ca...
I applied via Naukri.com and was interviewed before Nov 2020. There were 3 interview rounds.
I applied via Walk-in and was interviewed before May 2019. There were 5 interview rounds.
I applied via Walk-in and was interviewed before Feb 2021. There were 2 interview rounds.
I applied via Walk-in and was interviewed before Jun 2020. There were 5 interview rounds.
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