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I applied via LinkedIn and was interviewed in Feb 2022. There was 1 interview round.
Machine learning is a subset of artificial intelligence that involves training algorithms to make predictions or decisions based on data.
Machine learning involves using algorithms to learn patterns in data
It can be supervised, unsupervised, or semi-supervised
Examples include image recognition, natural language processing, and recommendation systems
Missing values can be handled by imputation or deletion.
Imputation involves filling in missing values with estimated values based on other data points.
Deletion involves removing rows or columns with missing values.
The choice of method depends on the amount and pattern of missing data.
Imputation methods include mean imputation, regression imputation, and k-nearest neighbor imputation.
Deletion methods include listwise de...
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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...
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