recurrent neural networks – معتز خالد سعد

Algobeans

What better way for machines to learn than to emulate the human brain? Artificial neural networks, as its name suggests, is a machine learning technique which is modeled after the brain structure. It comprises of a network of learning units called neurons. These neurons learn how to convert input signals (e.g. picture of a cat) into corresponding output signals (e.g. the label “cat”), forming the basis of automated recognition.

Let’s take the example of automatic image recognition. The process of determining whether a picture contains a cat involves an activation function. If the picture resembles prior cat images the neurons have seen before, the label “cat” would be activated. Hence, the more labelled images the neurons are exposed to, the better it learns how to recognize other unlabelled images. We call this the process of training neurons. (For an in-depth explanation, check out our tutorial on Artificial Neural Networks

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Tag: recurrent neural networks

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