Introduction of an Artificial Intelligence term has changed many aspects of IT industry. Artificial intelligence framework is the most growing and upcoming trend in the IT business industry. It accomplishes numerous technical aspects of the technology with huge branches in various fields of internet technology like Machine learning, Deep learning, Voice recognition technologies, Image processing techniques, robotics and most important Neural networks.
Artificial Neural Network
The main objective of an artificial neural network is to develop a computational model which can understand same as human brain interpret things. Since human brain processes information through its nerve cells that reside in it and are called as neurons. And so are the artificial neural networks that are influencing in designing a network architecture which also works same as the neurons work in the brain of a human. Artificial neural network uses the same techniques as human brain uses to understand information but in the form of algorithms which are further used in recognizing complex patterns and various predictions. In more specific terms, a neural network is a cluster of algorithms that can understand interconnected information between data sets as human brain understand relationships.
How neural network is different from human brain?
Human brain performs many kinds of activities on its own without instructions whereas neural networks work the way they are programmed to do, but it works fast as compared to human brain. Human brain can think on its own and take help from various internet resources for solving its complex queries. Researchers take help from various websites for understanding basic concepts like write my essay for me. Furthermore, lets have look on basic difference between human brain and artificial neural networks.
| Sr. no. | Artificial Neural Networks | Human Brain |
| 1. | Information processing time is too fast and respond in nanoseconds. | Information processing time is slower and reply in millisecond. |
| 2. | Compact in size & complexity. | Most complicated & dense network having billions of interconnected neurons. |
| 3. | Information stored in it is versatile. Accomplished with specific storage memory. | Information could never be stolen and there is no limit for storage |
| 4. | It works with the help of control unit for performing computational tasks. | Does not require any controlling unit. |
Applications of Neural Networks
An artificial neural network is the most sensitive field of artificial intelligence. It has expanded its branches in various fields of computational networks for practical deployment of its applications such as voice recognition, digital signature verifications, face recognition, foreign currency exchanging systems, weather forecasting patterns & optimization problem solving techniques. Moreover, it is also used in credit card frauds detections and performing secure financial transaction in banking sectors. Since it can solve very complex problem in nanosecond so research oriented students are taking too much interests in its computational strategies for solving their educational stuffs and mean students also assist assignment help for core concepts understandings.
Downside
Artificial neural networks accomplished with lesser fault tolerance. Moreover, neural networks use black box feature which have more computational load & data overflowing is the major problem. Error detection is too difficult in neural networks.
