What is Neural Network?
Neural networks are a series of algorithms that mimic the operations of a human brain to recognize relationships between vast amounts of data.
Neural networks can be taught to perform complex tasks and do not require programming as conventional computers. They are massively parallel, extremely fast, and intrinsically fault-tolerant. They learn from experience, generalize from examples, and are able to extract essential characteristics. A neural network is made up of a number of processing elements called neurons, whose interconnections are called synapses. Each neuron accepts inputs from either the external world or from the outputs of other neurons. Output signals from all neurons eventually propagate their effect across the entire network to the final layer where the results can be output.
Applications for Artificial Neural Networks (ANNs)
Artificial neural networks have been applied in all areas of operations.
- Email service providers use ANNs to detect and delete spam from a user’s inbox.
- Asset managers use it to forecast the direction of a company’s stock.
- Credit rating firms use it to improve their credit scoring methods.
- E-commerce platforms use it to personalize recommendations to their audience.
- Chatbots are developed with ANNs for natural language processing.
- Deep learning algorithms use ANN to predict the likelihood of an event; and the list of ANN incorporation goes on across multiple sectors, industries, and countries.
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