This is in contrast to machine learning which requires

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Which gives them a different name even though the two seem to do the same job. Here the difference between them dear reader is the method of work and the distinctive characteristics of each of them. In terms of human intervention computing power used amount of data required and running time. Deep learning relies on special and very complex algorithms. It requires extreme complexity and interconnectedness to be able to mimic the way the mind works.


This is in contrast to machine learning algorithms which are usually simpler such as linear prediction and decision trees. Deep learning also requires very less human intervention than machine learning as it alone takes care of the pr Belgium WhatsApp Number Data ocess of extracting features or features. The other big difference is related to the size of the data. Deep learning requires a very large amount of data which therefore requires very large computing power to process this data.





This makes it require special devices other than the household or economic ones that we use.  a smaller amount of data and therefore much less computing power. This huge amount of data contributes to reducing human intervention in the processes of explaining characteristics or features to the machine and therefore deep learning is more advanced than machine learning. It usually learns itself with minimal human intervention in its processes but this can turn from an advantage into a disadvantage because the machines logic may be very different from human logic.