Difference between revisions of "History of Computers - Artificial Neural Network"
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==Introduction== | ==Introduction== | ||
| − | Artificial neural networks (ANNs) are a type of machine learning that loosely mirror biological neural networks. ANNS are useful at solving problems that the creator dose not completely understand. ANNs are also useful when dealing with incomplete or crazy data. | + | Artificial neural networks (ANNs) are a type of machine learning AI[[History of Computers - Artificial Intelligence]] that loosely mirror biological neural networks. ANNS are useful at solving problems that the creator dose not completely understand. ANNs are also useful when dealing with incomplete or crazy data. ANNs solve problems by adapting – or learning. ANNs learn through trial and error. Every training run is slightly different than the one before it. The training process is repeated until the network outputs the desired product. |
| − | ANNs solve problems by adapting – or learning. ANNs learn through trial and error. Every training run is slightly different than the one before it. The training process is repeated until the network outputs the desired product. | + | |
==Overview== | ==Overview== | ||
| + | |||
==Significance== | ==Significance== | ||
==References== | ==References== | ||
Revision as of 21:11, 17 September 2018
Introduction
Artificial neural networks (ANNs) are a type of machine learning AIHistory of Computers - Artificial Intelligence that loosely mirror biological neural networks. ANNS are useful at solving problems that the creator dose not completely understand. ANNs are also useful when dealing with incomplete or crazy data. ANNs solve problems by adapting – or learning. ANNs learn through trial and error. Every training run is slightly different than the one before it. The training process is repeated until the network outputs the desired product.
