1.Dependency on Data
Deep Learning Machine Learning
Comparatively large amount of data is needed plus with increase in input data performance increases.
A sufficient amount of data can build a good model. But more than what is needed won’t improve performance as such.
2.DEPENDENCY ON HARDWARE
DEEP LEARNING
High-end machines are a must.
MACHINE LEARNING
Canworkon small-end machines.
3.APPROACH USED
DEEP LEARNING
In deep learning, the problem is solved in one go by using several layers of neurons
MACHINE LEARNING
A large problem is subdivided into several small tasks and in the end, are combined to build the ML model
4.FEATURIZATION
DEEP LEARNING
Deep learning learns from the data itself and does not need external intervention.
MACHINE LEARNING
External intervention is necessary to provide the right input.
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