
Rectified Linear Unit, Sigmoid and Tanh are three activation functions that play an important role in how neural networks work....

Machine Learning is here to stay. More and more organizations are grasping the benefits of the technology, as long as...

The neurons of neural networks perform operations that are linear: they multiple an input vector with a weights vector and...

Flatten-T Swish is a new (2018) activation function that attempts to find the best of both worlds between traditional ReLU...

Over the last few years, we’ve seen the rise of a wide range of activation functions – such as FTSwish....

Exponential Linear Unit is a new type of activation function that attempts to resolve both the defects of traditional ReLU...

Rectified Linear Unit, or ReLU, is considered to be the standard activation function of choice for today’s neural networks. Even...

Deep neural networks perform linear operations to combine weight vectors with input vectors. The values that are the outputs of...

Even though the traditional ReLU activation function is used quite often, it may sometimes not produce a converging model. This...

The Leaky ReLU is a type of activation function which comes across many machine learning blogs every now and then....