The advantages and disadvantages of deep learning.
by SMEBOOK (admin) · February 27, 2021
- Features are automatically deduced and optimally tuned for desired outcome.
- The same neural network based approach can be applied to many different applications and data types.
- The deep learning architecture is flexible to be adapted to new problems in the future.
- It requires very large amount of data in order to perform better than other techniques.
- It is extremely expensive to train due to complex data models.
- There is no standard theory to guide you in selecting right deep learning tools as it requires knowledge of topology, training method and other parameters.
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