Until now, these terms have sometimes been used interchangeably, although there are notable differences. In fact, deep learning is a very particular type of machine learning which aims to replicate the way the brain works and apply this insight to computers. It uses neural networks, which contain artificial neurons organized in layers.
A neural network has three categories of neurons: the input layer, the hidden layers, and the output layer. The input layer receives bits of information to be analyzed and assigns probability weights, sending the result to the hidden layers. Here, this process is repeated and sent to the output layer.
Let’s take a closer look at the strengths and challenges of using deep learning.
The pros of using deep learning
Deep learning is recommended for the recognition of text, images, video, and audio. By adapting the number of layers – called architecture – the ...