Media & Marketing

Author

Carlos Barge

Modeled in accordance with the human brain, a Neural Network was built to mimic the functionality of a human brain. The human brain is a neural network made up of multiple neurons, similarly, an Artificial Neural Network (ANN) is made up of multiple perceptrons (explained later).

Modeled in accordance with the human brain, a Neural Network was built to mimic the functionality of a human brain.

A neural network consists of three important layers:

a) Input Layer: As the name suggests, this layer accepts all the inputs provided by the programmer.

b) Hidden Layer: Between the input and the output layer is a set of layers known as Hidden layers. In this layer, computations are performed which result in the output.

c) Output Layer: The inputs go through a series of transformations via the hidden layer which finally results in the output that is delivered via this layer.

In information technology, a neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Neural networks — also called artificial neural networks — are a variety of deep learning technologies.

Commercial applications of these technologies generally focus on solving complex signal processing or pattern recognition problems. Examples of significant commercial applications since 2000 include handwriting recognition for check processing, speech-to-text transcription, oil-exploration data analysis, weather prediction and facial recognition.

A neural network usually involves a large number of processors operating in parallel and arranged in tiers. The first tier receives the raw input information, just like optic nerves in human visual processing. Each successive tier receives the output from the tier preceding it, rather than from the raw input — in the same way neurons farther away from the optic nerve receive signals from those closer to it. The last tier produces the output of the system.

Neural networks are notable for being adaptive, which means they modify themselves as they learn from initial training and subsequent runs provide more information about the world. The most basic learning model is centered on weighting the input streams, which is how each node weights the importance of input from each of its predecessors. Inputs that contribute to getting right answers are weighted higher.

Free Pre-Assessment Request

Do you want to know how your competitors are doing business?

Tell us a little about yourself below to gain data for free


Hi What’s your name?

Next

Hi [First Name], what is your company’s name and website?

Previous

Next

Is your company looking for any data on the following services:

Previous

Next

Gotcha! Do you want to monitor any specific competitor or market?

List of Competitors

  • Add competitor…

Previous

Next

Finally, what’s your email address and your phone number?

Previous

Send

Your Data is on the Way!

Our data scientists team is working for you by collecting data and we’ll come back to you shortly with a pre-assessment and proposal.

WYgroup BI uses the information you provide to us to contact you about our relevant content, products, and services . You can unsubscribe from communications from HubSpot at any time. For more information, check out WYgroup’s Privacy Notice.
Comments

Leave a Comment:

Your email address will not be published. Required fields are marked *