If previously, the information was a commodity with a value limited to its instantly accessible features, now it is a resource the value of which depends on one’s skill to interpret it - the ability to make the most out of the available information.
This process requires complex systems that consist of multiple layers of algorithms, that together construct a network inspired by the way the human brain works, hence its name - neural networks.
Vector is an abstract representation of raw data that reiterates its meaning into a comprehensive form for the machine.
Unlike other types of neural networks that process data straight, where each element is processed independently of the others, recurrent neural networks keep in mind the relations between different segments of data, in more general terms, context.
Just like traditional Artificial Neural Networks, RNN consists of nodes with three distinct layers representing different stages of the operation.
Overall, the RNN neural network operation can be one of the three types:
Now let's take a look at the most prominent business applications of CNNs - convolutional neural networks and see how it is applied and what kind of benefits it brings to the business.