NEURAL NETWORK

 

INTRODUCTION ON NEURAL NETWORK:

·       Scientists agree that our brain has around 100 billion neurons.

 

·       These neurons have hundreds of billion connections between them.

 

·       Neurons (aka Nerve Cells) are the fundamental units of our brain and nervous system.

 

·       The neurons are responsible for receiving input from the external world, for sending output (commands to our muscles), and for transforming the electrical signals in between.

 

·       Basically, neural network works same as like Neurons receive the message from the external source and then interpret and gives an output.



·       Artificial Neural Networks are normally called Neural Networks (NN).

 

·       Neural networks are in fact multi-layer Perceptron.

 

·       The perceptron defines the first step into multi-layered neural networks.

 

·       Neural Networks is the essence of Deep Learning.

 

·       Neural Networks is one of the most significant discoveries in history.

 

·       Neural Networks can solve problems that can NOT be solved by algorithms:

Medical Diagnosis

Face Detection

Voice Recognition

What are Neural Networks?

Neural network basically mimics the function of human brain. They are used to solve various real-time tasks because of its ability to perform computations quickly and its fast responses.

Artificial Neural Network has a huge number of interconnected processing elements, also known as Nodes. These nodes are connected with other nodes using a connection link. The connection link contains weights, these weights contain the information about the input signal. Each iteration and input in turn leads to updating of these weights. After inputting all the data instances from the training data set, the final weights of the Neural Network along with its architecture is known as the Trained Neural Network. This process is called Training of Neural Networks. This trained neural network is used to solve specific problems as defined in the problem statement. Types of tasks that can be solved using an artificial neural network include Classification problems, Pattern Matching, Data Clustering, etc.

CONCLUSION

Artificial neural networks are created to digitally mimic the human brain. They are currently used for complex analyses in various fields, ranging from medicine to engineering, and these networks can be used to design the next generation of computers. We can use them to recognize handwriting, which can be useful in industries such as banking. Artificial neural networks can also do many important things in the field of medicine. We could use them to build models of the human body that could help doctors accurately diagnose diseases in their patients.

REFERENCE

·       https://www.w3schools.com/ai/ai_neural_networks.asp

·       https://kids.frontiersin.org

VIKASH KUMAR

INTERNATIONAL SCHOOL OF MANAGEMENT EXCELLENCE

 

INTERN@HUNNARVI TECHNOLOGIES UNDER THE GUIDANCE OF NANOBI DATA ANALYTIC PVT LTD.

Views are personal.

#neuralnetwork #usesofneuralnetwork #hunnarvi #isme

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