Search

Deep Neural Networks are nonlinear Activation Functions

Almost any process imaginable can be represented as a functional computation in a neural network, provided that the activation function is non-linear.


https://en.wikipedia.org/wiki/Activation_function


Non-linear functions address the problems of a linear activation function:

  1. They allow backpropagation because they have a derivative function which is related to the inputs.

  2. They allow “stacking” of multiple layers of neurons to create a deep neural network. Multiple hidden layers of neurons are needed to learn complex data sets with high levels of accuracy.


https://missinglink.ai/guides/neural-network-concepts/7-types-neural-network-activation-functions-right/

Recent Posts

See All

Biotech & BioInformatics

Life itself is a technology now. Biotech has changed medicine. Contrary to common sense, perhaps, the notion that data has absolute value is simply not true. Data is only as valuable as the insight yo

DevOps

DevOps is a collaboration of the development (Dev) and operations (Ops) teams with its foundation depending on providing IT automation. DevOps is an agile methodology that includes a set of practices