NEURAL NETWORK 101

Neural networks are computing systems that try to emulate brain functions. Neural networks are trained using real-world data, and once trained, they can perform faster than conventional methods. Neural networks can do classification, pattern recognition, approximation, clustering, prediction, and optimization. Neural networks are composed up of layers, and each layer contains neurons and nodes. These neurons and nodes make communication between different layers possible. Every node has a weight associated with it. This weight decides the importance of input. Every neuron has an internal state, also known as an activation function. The output is generated when the input signal is processed through the activation function... A human brain contains billions of neurons, and each neuron can have thousands of interconnections. A human neuron has the following components, a dendrite that receives information, a soma that processes information, an axon that works as a cable for sending and..