Neural networks are foundational to artificial intelligence (AI) today, from the way they intuitively learn to aid so many of your everyday life applications, whether it be virtual assistants and recommendation systems or autonomous vehicles and healthcare diagnostics. These are computer programs that mimic the structure of an animal brain so well, they can recognize patterns and manipulate large amounts of data very efficiently.
In plain English, neural networks are a set of algorithms, modeled loosely after the human brain. They consist of layers of nodes (like neurons) forming a network. It is a directed graph, where every node in one layer processes the generated data and passes it on to be further refined by nodes of the next layers, which finally reaches a conclusion or prediction from what has been learned.
Machine Learning (ML) and Deep Learning deeply rely on neural networks. They perform well on tasks like image classification, speech recognition, or language translation by learning from the data you feed them.
Neural networks contain three types of layers:
A weight is associated with each connection between neurons, determining how much influence a specific input has on the ultimate output. This phase is called training of the model, during which a network adjusts these weights using techniques such as back-propagation and gradient descent to minimize error. The repetition of this process allows the network to learn how to properly map inputs and outputs.
Neural networks continue to revolutionize industries, offering unprecedented capabilities in data processing and decision-making. To explore how eMazzanti can help your organization leverage the power of AI and neural networks, contact us today.
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