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I applied via Approached by Company and was interviewed before May 2023. There were 3 interview rounds.
Bias and variance are two sources of error in machine learning models. Different machine learning algorithms have different assumptions. CNN architecture consists of convolutional layers, pooling layers, and fully connected layers.
Bias is the error due to overly simplistic assumptions in the model, while variance is the error due to overly complex assumptions.
Different machine learning algorithms have different assumpt...
I applied via Referral and was interviewed in Apr 2023. There were 2 interview rounds.
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...
I appeared for an interview in Mar 2017.
To make the red fishes 98%, 50 fishes have to be removed from the aquarium.
Calculate 1% of 200 fishes, which is 2 fishes.
To make the red fishes 98%, subtract 1% (2 fishes) from 99% (198 fishes).
To find the number of fishes to be removed, divide the difference by 1% (2 fishes).
Therefore, 50 fishes have to be removed to make the red fishes 98%.
I appeared for an interview in Feb 2017.
I appeared for an interview in Mar 2017.
To make the red fishes 98%, 50 fishes have to be removed from the aquarium.
Calculate 1% of 200 fishes to find the number of red fishes.
Subtract the number of red fishes from 200 to find the number of non-red fishes.
Calculate 2% of the total number of fishes to find the desired number of red fishes.
Subtract the desired number of red fishes from the current number of red fishes to find the number of fishes to be removed.
posted on 3 May 2017
I appeared for an interview before May 2016.
posted on 28 Jun 2017
I appeared for an interview in Mar 2017.
To make the red fishes 98%, 50 fishes have to be removed from the aquarium.
Calculate 1% of 200 fishes to find out how many fishes represent 1%.
Multiply the result by 2 to find out how many fishes represent 2%.
Subtract the result from 200 to find out how many fishes represent 98%.
I appeared for an interview before May 2016.
I appeared for an interview in Jul 2017.
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