- Deep learning algorithms are capable of learning arbitrarily complex non-linear functions by using a deep enough and a wide enough network with the appropriate non-linear activation function.
- Traditional ML algorithms often require feature engineering of finding the subset of meaningful features to use. Deep learning algorithms often avoid the need for the feature engineering step.
- Deep Learning algorithms do well when there is a lot of data to work with.
When are deep learning algorithms more appropriate compared to traditional machine learning algorithms?
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