Machine Learning Hive

In machine learning, the perceptron is an algorithm for supervised learning of binary classifiers. It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector. The Perceptron, also known as the Rosenblatt’s Perceptron . Perceptrons are the most primitive classifiers, akin to the base neurons in a deep-learning system. What is Perceptron  A Single Neuron The basic unit of computation in a neural network is the neuron , often called a node or unit . It receives input from some other nodes, or from an external source and computes an output. Each input has an associated weight  (w), which is assigned on the basis of its relative importance to other inputs. The node applies a function  f (defined below) to the weighted sum of its inputs as shown in Figure 1 below: Basic elements of Perceptron Inputs : X1,...

In neuroscience, a neural network is a series of interconnected neurons whose activation defines a recognizable linear pathway. The interface through which neurons interact with their neighbors usually consists of several axon terminals connected via synapses to dendrites on other neurons. If the sum of the input signals into one neuron surpasses a certain threshold, the neuron sends an action potential (AP) at the axon hillock and transmits this electrical signal along the axon. But in terms of AI, neural network refers to Artificial Neural Network. So, what is Artificial Neural Network  The simplest definition of a neural network, more properly referred to as an 'artificial' neural network (ANN), is provided by the inventor of one of the first neurocomputers, Dr. Robert Hecht-Nielsen. He defines a neural network as: a computing system made up of a number of simple, highly interconnected processing elements, which process information by their dynami...