If you are new to the field of Deep Learning, I encourage you to read my previous article about Understand Deep Leaning with Simple exercise-PyTorch which will give you a precise understanding of how neural networks works in general. This article is a more deep dive into the internal working of Neuron/Perceptron which is the building block of Deep Learning Neural Networks architecture. A human brain has billions of neurons. Neurons are interconnected nerve cells in the human brain that are involved in the processing and transmitting chemical and electrical signals. Dendrites are branches that receive information from other neurons.
Every invention is a consequence of a fact which pre-exist in our surroundings. Artificial Neural Network is one of those discoveries. We will study ANN in-depth, but before that, it's important to study about, the origin of its discovery. There are a lot of questions I need to answer, before we move towards the question, "What is Artificial Neural Network?" The human brain is the master control system in the human body, which controls and manages almost every action of ours.
In Modern times, the influence of artificial intelligence has already demonstrated remarkable and tremendous progress. This field of artificial intelligence has been deeply influenced by neural networks. Neural networks have been the most important tool in the development of Artificial intelligence. Neural networks simply reflect the behavior of the human brain by the computer machines to recognize patterns and solve daily based common problems in the fields of AI. Neural networks are the subset of machine learning and are said to be the heart of deep learning. The neural network can also be recognized as a mathematical function that simply converts a set of inputs into output components. A neural network is a data processing system consisting of a large number of simple, highly interconnected processing elements called as nodes. Further we will be understanding in depth about neural networks.
In this article we'll have a quick look at artificial neural networks in general, then we examine a single neuron, and finally (this is the coding part) we take the most basic version of an artificial neuron, the perceptron, and make it classify points on a plane. Have you ever wondered why there are tasks that are dead simple for any human but incredibly difficult for computers? Artificial neural networks (short: ANN's) were inspired by the central nervous system of humans. Like their biological counterpart, ANN's are built upon simple signal processing elements that are connected together into a large mesh. ANN's have been successfully applied to a number of problem domains: Agreed, this sounds a bit abstract, so let's look at some real-world applications.