Neural Networks and Deep Learning are currently the two hot buzzwords that are being used nowadays with Artificial Intelligence. The recent developments in the world of Artificial intelligence can be attributed to these two as they have played a significant role in improving the intelligence of AI. Look around, and you will find more and more intelligent machines around. Thanks to Neural Networks and Deep Learning, jobs and capabilities that were once considered the forte of humans are now being performed by machines. Today, Machines are no longer made to eat more complex algorithms, but instead, they are fed to develop into an autonomous, self-teaching systems capable of revolutionizing many industries all around.

Artificial Neural Networks are the computational models inspired by the human brain. Many of the recent advancements have been made in the field of Artificial Intelligence, including Voice Recognition, Image Recognition, Robotics using Artificial Neural Networks. These biological methods of computing are considered to be the next major advancement in the Computing Industry. The term'Neural' is derived from the human (animal) nervous system's basic functional unit'neuron' or nerve cells which are present in the brain and other parts of the human (animal) body. It receives signals from other neurons. It sums all the incoming signals to generate input.

Artificial Neural Networks are the computational models inspired by the human brain. Many of the recent advancements have been made in the field of Artificial Intelligence, including Voice Recognition, Image Recognition, Robotics using Artificial Neural Networks. These biological methods of computing are considered to be the next major advancement in the Computing Industry. The term'Neural' is derived from the human (animal) nervous system's basic functional unit'neuron' or nerve cells which are present in the brain and other parts of the human (animal) body. It receives signals from other neurons. It sums all the incoming signals to generate input.

The term'Neural' is derived from the human (animal) nervous system's basic functional unit'neuron' or nerve cells which are present in the brain and other parts of the human (animal) body. Dendrite - It receives signals from other neurons. Soma (cell body) - It sums all the incoming signals to generate input. Axon - When the sum reaches a threshold value, neuron fires and the signal travels down the axon to the other neurons. The amount of signal transmitted depend upon the strength (synaptic weights) of the connections.

Inspired by the structure of the brain, artificial neural networks (ANN) are the answer to making computers more human like and help machines reason more like humans. They are based on the neural structure of the brain. The brain basically learns from experience. It is natural proof that some problems that are beyond the scope of current computers are indeed solvable by small energy efficient packages. To understand how artificial neural networks work let's first briefly look at the human ones. The exact workings of the human brain are still a mystery. Yet, some aspects of this amazing processor are known. In particular, the most basic element of the human brain is a specific type of cell which, unlike the rest of the body, doesn't appear to regenerate.