The idea behind the neural network is that many brain cells are interconnected inside the computers using that you can learn things, make a decision like a human, and recognise the pattern. The main aim of the neural network is that you don’t have to program it to learn explicitly you have to learn all by itself just like the brain. The neural network uses ordinary computers and you can find freelancers from different job portals in this niche skill.

Artificial Neural Network inspires from a biological nervous system such as process information, and it is an information processing device. The large Artificial Neural network has hundreds of thousands of processor unit such as mammalian brain has billions of neuron with a corresponding increase in their overall interaction. The application of Artificial Neural network is that data classification and pattern recognition using learning process. Learning in biological systems means changes to the synaptic connection that exist between the neurons.

History of Neural Network:-                                                                                                           

Warren McCulloch along with Walter Pitts in 1943 published a paper on how neuron might work.  Donald Hebb describes the Organisation of behaviour concept in 1949 which describes the neural pathway get strengthened each time they have used a concept fundamentally essential to how humans learn.

The first step to stimulate hypothetical neural network made Nathanial Rochester from IBM research laboratories, but his first attempt failed. IN 1950 computer become more advanced because of this, it is easy to make a hypothetical neural network. Widrow and Hoff in 1962 create learning processes that examine the value before the weight adjusts it.

Kohonen and Anderson in 1972 both were created similar network independently. They both used matrix mathematics to explain their ideas but did not realise what they are doing was and crating array of analogue ADLINE circuits. In 1975 an unsupervised network developed as a first multi-layered network.

The architecture of Neural network:-

Feed- Forward Network:-

Feed- forward network does not give any feedback that does not use a loop, and it allows signals to travel one way only from input to output, so the output of any layer does not affect that same layers. It associates input with output and feeds forward artificial neural network is a straight forward neural network. You can use it for pattern recognition, and it is also known as top down and bottom up approach. You can hire freelancers online who have knowledge of architecture.

Feedback Network:-

Feedback network consists of a loop which is useful for traveling signals from both directions. It is very complicated and powerful network. Until they reach an equilibrium point, their state is changing, so feedback network is dynamic.  It is at equilibrium point unless and until input changes a new equilibrium found. Feedback architecture denotes feedback connection in single layer organisation, and it is also known as interactive.

 Network Layer:

The artificial neural network consists of three layers in which layer of input units connect to a layer of hidden units, and it also connects to the layer of an output unit. The input layer feeds the raw information into the networks. Hidden layer determined what the activity of input units and weight on the connections between the input and hidden units. The activity of output unit depends on the hidden unit and the weights between the hidden and output units.

The network layer is a simple type of network is excellent because the hidden units are free to construct their representation of the input. When each hidden unit is active the weight between the input and hidden units determine. Here is also a single and multi-layered architecture in single layer architecture all units connect with one another. In multi-layered architecture, each unit is numbered by layers instead of following a global numbering. Find freelancers in these areas as you can’t find people with a lot of experience in these latest technologies.

Perceptrons:

Frank Rosenblatt developed this basic concept. It describes the basic idea behind the mammalian visual system. It is mainly beneficial for pattern recognition and though their capability extended a lot more. Minsky and Papert in 1969 described the limitation of single layer perceptrons. Some basic pattern recognition operation determines whether the shape is connected or not.

Application of Neural network:

There are a lot of application for a neural network that is useful for recognising the pattern and making a simple decision about them.

The neural network in Manufacturing:

In airplanes, the system uses a neural network as basic autopilot. In output units adapting the planes control properly to keep it safety on the course and input units reading signals from the various cockpit instruments. In factory neural network is used for quality control suppose the factory producing detergent which is convoluted by a chemical process.  Measure the final detergent in a various parameter such as colour, thickness, and acidity this parameter feed as input to the neural network and then neural system check and decide whether the batch is accepted or rejected.

The neural network in Medicine:

In medicine area, artificial neural network is the hot research area. In next few years, the biomedical system receives an extensive application. Now researcher works on creating modelling parts of the human body and finding disease from various scans. There are no needs to provide a specific algorithm how to identify the disease.

Neural Network in Practice:

For identifying the pattern or trends in data, the neural network plays an important role. It plays an important role in customer research, sales forecasting, industrial process control, data validation, and risk management.

Neural Network in Marketing:

There are a lot of applications of the neural network in marketing. The Airline Marketing Tactician application is integrated with neural network and trained using back- propagation to assist the control of airline seat allocation. The adaptive neural approaches apply to rule expression. The system is used to monitor and counsel booking advice for each departure. You can hire freelancers online in this area.

Summary:

In this article, you get information regarding what is neural network and what is the artificial neural network. You also get information relating to the architecture of the neural network and different application of neural network in daily life.

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