Artificial Neural Network (ANN) - To The Point | Drishti IAS English

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Neural Networks is a computational learning system, which uses a network of functions to understand and translate a data input of one form into a desired output. The ANN models have the specific architecture format, which is inspired by a biological nervous system.

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This video covers the given topic, ‘Artificial Neural Network’, in the following structure:


1. Why in the News ?

2. What is an Artificial Neural Network (ANN) ?

3. What is Backpropagation?

4. Applications/Uses of ANN

5. Advantages and Disadvantages of ANN

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#ANN #NeuralNetwork #Backpropagation #ToThePoint #CurrentAffairs
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"Option C" Both statements are correct.. :)

sauravgupta
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Option c is right ans for given question, thanks mam

shivangipatel
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🛃🛃🛃 *What is an Artificial Neural Network* ? 🛃🛃🛃

It is a vital subset of machine learning that helps computer scientists in their work on complex tasks, such as, strategizing, making predictions, and recognizing trends.

It is a computational model that mimics the way nerve cells work in the human brain. It is designed to simulate the way the human brain analyzes and processes information.

It is not like other machine learning algorithms that crunch numbers or organise data,  it is an algorithm that learns from experience and repeated tasks performed by its users.

It is also known as a Neural Network (NN). ANN is a computational model based on the functions and structure of biological neural networks.

Information that runs through the network affects the structure of the artificial neural network due to the fact that a neural network learns or changes based on the input and output.

NNs are fed massive volumes of data in the beginning phases. In most cases,  training is done by providing input and informing the network about what should be the output.

Many smartphone makers, for example, have recently integrated facial recognition technology.

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