Neural networks
Artificial neural networks are computational models inspired by the structure and functioning of the human brain. They are composed of artificial neurons, organized into layers (input, hidden and output), which process information by simulating the way biological neurons communicate with each other. Each neuron receives input, processes it through mathematical functions and transmits an output to other neurons in the next layer. This structure allows neural networks to learn autonomously from data, identifying complex patterns that are difficult to detect with traditional techniques.
In the context of SEO, neural networks are used by search engines to improve their understanding of natural language and user queries. For example, algorithms such as Google’s RankBrain and BERT rely on neural architectures to better interpret the meaning of words and the context of phrases, returning more relevant results.
This technology continues to evolve, making it essential to adapt to new search engine logic to improve online ranking
