Why might a deep learning practitioner use regularization techniques on a model?
- To make the model larger
- To simplify the model
- To prevent overfitting
- To increase training speed
Deep learning practitioners use regularization techniques to 'prevent overfitting.' Overfitting is when a model learns noise in the training data, and regularization helps in making the model more generalized and robust to new data.
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