What is it?

• Neural networks, also known as artificial neural networks (ANNs) or simulated neural networks (SNNs), are a subset of machine learning and are at the heart of deep learning algorithms. Their name and structure are inspired by the human brain, mimicking the way that biological neurons signal to one another.
• The concept behind an Artificial Neural Network is to define inputs and outputs, feed pieces of inputs to computer programs that function like neurons and make inferences or calculations, then forward those results to another layer of computer programs and so on, until a result is obtained. As part of this neural network, a difference between intended output and input is computed at each layer and this difference is used to tune the parameters to each program. This method is called backpropagation and is an essential component to the Neural Network.
• ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain.
• ANNs are created by programming regular computers to behave as though they are interconnected brain cells
• ANNs are present in many smartphone applications that we use, like voice to type, Siri and Alexa.

What is Machine learning

• Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.

Why in News:

• MIT Researchers introduced a Machine Learning Technique that can Automatically Describe the Roles of Individual Neurons in a Neural Network with Natural Language

References:

1. https://www.ibm.com/cloud/learn/neural-networks
2. https://www.thehindu.com/sci-tech/technology/understanding-artificial-neural-networks/article38390874.ece